2017
Gordana-Raluca
Barb
T´
ecnicas Lineares de Equaliza¸
c˜
ao para Sistemas
H´ıbridos de Comunica¸
c˜
ao na Banda das Ondas
Milim´
etricas
Linear Equalization Techniques for Hybrid Systems
in the Millimeter Wave Band of Communications
“We should insist more on education. It is the answer to so many world problems.” — Gordana-Raluca Barb 2017
Gordana-Raluca
Barb
T´
ecnicas Lineares de Equaliza¸
c˜
ao para Sistemas
H´ıbridos de Comunica¸
c˜
ao na Banda das Ondas
Milim´
etricas
Linear Equalization Techniques for Hybrid Systems
in the Millimeter Wave Band of Communications
2017
Gordana-Raluca
Barb
T´
ecnicas Lineares de Equaliza¸
c˜
ao para Sistemas
H´ıbridos de Comunica¸
c˜
ao na Banda das Ondas
Milim´
etricas
Linear Equalization Techniques for Hybrid Systems
in the Millimeter Wave Band of Communications
Disserta¸c˜ao apresentada `a Universidade de Aveiro para cumprimento dos requisitos necess´arios `a obten¸c˜ao do grau de Mestre em Engenharia Eletr´onica e Telecomunica¸c˜oes, realizada sob a orienta¸c˜ao cient´ıfica do Pro-fessor Doutor Ad˜ao Silva (orientador), Professor auxiliar do Departamento de Eletr´onica, Telecomunica¸c˜oes e Inform´atica da Universidade de Aveiro e do Doutor Daniel Castanheira (co-orientador), investigador no Instituto de Telecomunica¸c˜oes de Aveiro.
presidente / president Professor Doutor Jos´e Carlos Esteves Duarte Pedro
Professor Catedr´atico da Universidade de Aveiro
vogais / examiners committee Professor Doutor Marco Alexandre Cravo Gomes
Professor Auxiliar da Faculdade de Ciˆencias e Tecnologia da Universidade de Coimbra
Professor Doutor Ad˜ao Paulo Soares da Silva
First of all, my deepest appreciation to my family, in particular my parents, for all the support, motivation and effort they’ve made so I could succeed. A special gratitude I give to my advisor, Prof. Ad˜ao Silva, and co-advisor, Daniel Castanheira, for supervising the process of my dissertation and for the patience, advice and guidance.
Last but not least, many thanks to all my friends, teachers, colleagues that I have encountered in my life and helped me become who I am today. To all of you, I extend my deepest gratitude.
Resumo As comunica¸c˜oes sem fio est˜ao em constante evolu¸c˜ao, e a necessidade por elevadas taxas de transmiss˜ao de dados, mais capacidade, melhor qualidade de servi¸co e mais cobertura, est´a a aumentar. A pr´oxima gera¸c˜ao, 5G, est´a neste momento a ser desenvolvida e espera-se que seja implementada em 2020. No entanto, de forma a cumprir os requisitos do 5G, tais como proporcionar uma melhoria na experiˆencia do utilizador, taxas de transmiss˜ao m´aximas de 10 a 50 Gbps, maior fiabilidade e cobertura, s˜ao necess´arias mudan¸cas na arquitetura celular, utilizando para tal novas tecnologias. As ondas milim´etricas constituem uma frequˆencia portadora promissora para os sistemas celulares 5G, devido `a sua grande largura de banda dispon´ıvel, que potencialmente pode fornecer taxas de transmiss˜ao elevadas para os futuros sistemas sem fios.
Single-carrier frequency-division multiple access (SC-FDMA), um m´etodo modificado de orthogonal frequency-division multiple access (OFDMA), ´e uma t´ecnica promissora que poder´a ser uma solu¸c˜ao para comunica¸c˜oes com elevadas taxas de transmiss˜ao no sentido ascendente nos sistemas celulares futuros. Quando comparado com OFDMA, SC-FDMA possui um rendimento semelhante e apresenta essencialmente a mesma complexidade. A principal vantagem de SC-FDMA ´e o peak-to-average power ratio (PAPR), que ´e menor que no OFDMA, sendo menos sens´ıvel `as distor¸c˜oes n˜ao-lineares causadas pelo amplificador de potˆencia (AP). Sabe-se que a eficiˆencia do AP ´e um problema cr´ıtico para os futuros sistemas sem fio baseados em ondas milim´etricas. Conjugando ondas milim´etricas com massive MIMO permitir´a colocar um maior n´umero de antenas no mesmo volume, uma vez que as ondas milim´etricas tˆem um comprimento de onda menor do que os sistemas celulares usados atualmente. Conse-quentemente, as comunica¸c˜oes que usam ondas milim´etricas e massive MIMO s˜ao consideradas duas das principais tecnologias que oferecem as condi¸c˜oes necess´arias para fornecer multi-Gbps para os futuros sistemas de comunica¸c˜ao.
Nesta disserta¸c˜ao ´e projetado e avaliado um equalizador linear h´ıbrido anal´ogico-digital multi-user para sistemas massive MIMO SC-FDMA de banda larga usando ondas milim´etricas. Assume-se que a parte anal´ogica ´
e constante para todas as subportadoras, enquanto que a parte digital ´e calculada por cada subportadora. Os resultados mostram que a arquitetura proposta atinge uma taxa m´edia de erro pr´oxima do equalizador digital (separa¸c˜ao de ∼ 1 dB), quando o n´umero de cadeias RF ´e o dobro que o n´umero de utilizadores. Se o mesmo for inferior que o dobro dos utilizadores, um compromisso entre complexidade e desempenho ´e
Abstract Wireless communications are continuously evolving, and the demand for higher data rates, more capacity, a better quality of service and more coverage is rising. The next generation, 5G, is currently being developed and it is expected to be delivered by 2020. However, in order to fulfill the 5G requirements, such as a consistent user experience, peak bit rates of 10 to 50 Gbps, higher reliability and availability, changes in the cellular architecture are needed, using new technology. Millimeter waves are a promising carrier frequency for 5G cellular systems, due to their underutilized large bandwidth that can potentially provide high data rates for future wireless networks.
Single-carrier frequency-division multiple access (SC-FDMA), a modi-fied form of orthogonal frequency-division multiple access (OFDMA), is a promising solution technique for high data rate uplink communications in future cellular systems. When compared with OFDMA, SC-FDMA has similar throughput and essentially the same overall complexity. A principal advantage of SC-FDMA is the peak-to-average power ratio (PAPR), which is lower than that of OFDMA, being less sensitive to nonlinear distortion caused by the power amplifier (PA). It is well known that an efficient PA is critical for future millimeter wave based wireless systems. Conjugating mmWaves with massive MIMO will allow packing a higher number of antennas into the same volume, since mmWaves have a smaller wavelength than the currently used cellular systems. Consequently, millimeter wave communications and massive MIMO have been considered as two of the key enabling technologies needed to provide multi-Gbps for future wireless communications.
In this Dissertation a hybrid analog-digital multi-user linear equalizer for broadband mmWave massive MIMO SC-FDMA systems is designed and evaluated. The digital part is computed on a per subcarrier basis and the analog part is constant over all subcarriers. The simulation results show that the proposed hybrid equalizer achieves an average BER close to the full-digital equalizer (gap of ∼ 1 dB), when the number of RF chains is twice the number of users. When the number of RF chains is smaller than twice the number of users, a compromise between complexity and performance is achieved.
Contents i
List of Figures iii
List of Tables v
Acronyms vi
1 Introduction 1
1.1 Background and Evolution of Cellular Communications Systems . . . 1
1.2 5G: The Next Generation . . . 7
1.3 Motivation and Objectives . . . 9
1.4 Contributions . . . 10
1.5 Outline . . . 10
1.6 List of Notations . . . 11
2 Single and Multicarrier Systems 13 2.1 Orthogonal Frequency Division Multiplexing . . . 13
2.1.1 Modulation . . . 14 2.1.2 Orthogonality . . . 15 2.1.3 Cyclic Prefix . . . 16 2.1.4 OFDM Architecture . . . 17 2.2 OFDMA System . . . 18 2.3 SC-FDMA System . . . 20
2.3.1 Equalization Schemes used in SC-FDMA . . . 21
2.4 OFDMA and SC-FDMA Systems Comparison . . . 22
2.5 Modulation Techniques for the Future Wireless Communications Systems . . 23
2.5.1 Constant Envelope OFDM . . . 23
2.5.2 Filter Bank OFDM . . . 25
2.5.3 GOFDM . . . 27
3 Multiple Antenna Systems 29 3.1 Antenna Configurations . . . 29
3.2 Diversity . . . 30
3.2.1 Receive Diversity . . . 32
3.2.2 Transmit Diversity . . . 33
3.3.1 SU-MIMO Techniques . . . 36
Channel known at the Transmitter . . . 36
Channel not known at the Transmitter . . . 39
3.3.2 MU-MIMO Techniques . . . 40
3.4 Massive MIMO . . . 41
3.4.1 Potential of Massive MIMO . . . 43
3.4.2 Challenges of Massive MIMO . . . 45
3.4.3 Advantages and Disadvantages of Massive MIMO . . . 46
4 Millimeter Waves Systems 49 4.1 Millimeter Waves Spectrum . . . 49
4.1.1 Propagation Characteristics . . . 50
4.2 Millimeter Waves Applications . . . 52
4.3 Advantages and Disadvantages of Millimeter Waves . . . 53
4.4 Millimeter Waves with massive MIMO systems . . . 54
4.4.1 Antenna Designs . . . 54
4.4.2 Advanced Architectures . . . 55
5 Receive Beamforming Scheme for mmWave with Massive MIMO 59 5.1 System Model Characterization . . . 60
5.1.1 Transmitter Model Description . . . 60
5.1.2 Receiver Model Description . . . 61
5.1.3 Channel Modeling for mmWave Massive MIMO System . . . 62
5.1.4 Algorithm Description . . . 63
Hybrid Analog/Digital Equalizer . . . 63
5.2 Performance Results . . . 68
6 Conclusion and Future Work 73 6.1 Conclusion . . . 73
6.2 Future Work . . . 75
1.1 Evolution of Mobile Communications. . . 2
1.2 Global Connections by Technology (in millions) [10]. . . 3
1.3 How WiMAX works [14]. . . 4
1.4 Differences between FDD and TDD [19]. . . 5
1.5 LTE subscriptions estimates and forecasts, 2012-2019 (million subscribers). Source: IDATE Digiworld, in State of LTE & MBB spectrum worldwide, De-cember 2015 . . . 7
1.6 Cisco Forecasts 49 Exabytes per Month of Mobile Data Traffic by 2021. Source: Cisco VNI Mobile, 2017 . . . 8
1.7 Key Parameters for 5G Mobile Communications [27]. . . 9
2.1 OFDM modulation with Nc subcarriers. . . 14
2.2 OFDM spectrum [37]. . . 15
2.3 Cyclic Prefix. . . 16
2.4 OFDM Transmitter and Receiver Block Diagram. . . 17
2.5 OFDM and OFDMA comparison. . . 19
2.6 Types of subcarriers mapping [17]. . . 19
2.7 SC-FDMA Transmitter Block Diagram [17]. . . 20
2.8 SC-FDMA Receiver Block Diagram [17]. . . 21
2.9 Comparison between OFDMA and SC-FDMA [43]. . . 23
2.10 CE-OFDM and OFDM envelope comparison [48]. . . 24
2.11 Instantaneous power of OFDM and CE-OFDM systems [48]. . . 25
2.12 FB-OFDM modulation and demodulation diagram [51]. . . 26
2.13 GOFDM transmitter and receiver block diagram. . . 27
3.1 Antenna Configurations [57]. . . 30
3.2 Time diversity [5]. . . 31
3.3 Frequency diversity [5]. . . 31
3.4 Receive Diversity System [62]. . . 32
3.5 Alamouti scheme with 2 transmit antennas and 1 receive antenna - encoder [17]. 34 3.6 Alamouti scheme with 2 transmit antennas and 1 receive antenna - decoder [17]. 34 3.7 Alamouti scheme and code [17]. . . 34
3.8 Diversity-Multiplexing Trade-off. . . 36
3.9 Spatial Multiplexing System [17]. . . 37
3.10 Waterfilling schematic. . . 39
3.14 Downlink operation of a massive MIMO link [69]. . . 42
3.15 Uplink operation of a massive MIMO link [69]. . . 43
3.16 Trade-off between energy efficiency and spectral efficiency [68]. . . 44
3.17 Pilot contamination. [70]. . . 46
4.1 Millimeter waves spectrum [73]. . . 50
4.2 Rain attenuation for mmWaves [76]. . . 51
4.3 Atmospheric and molecular absorption by mmWaves [77]. . . 51
4.4 E-band wireless backhaul with high speed data transmission [79]. . . 52
4.5 Comparison between patch antenna and mmWave array antenna [30]. . . 54
4.6 Hybrid full-connected beamforming architecture. . . 55
4.7 Hybrid sub-connected beamforming architecture. . . 55
4.8 1-bit ADC hybrid architecture [84]. . . 56
5.1 Overview of the considered SC-FDMA UT. . . 61
5.2 Overview of hybrid analog-digital equalizer. . . 62
5.3 Performance of the proposed hybrid equalizer for scenario 1. . . 69
5.4 Performance of the proposed hybrid equalizer for scenario 2. . . 69
5.5 Performance of the proposed hybrid equalizer for scenario 3. . . 70
5.6 Performance of the proposed hybrid equalizer for scenario 4. . . 70
5.7 Eb/N0 as function of number of RF chains for scenario 3. . . 71
1.1 GSM World Coverage Table. . . 2
1.2 LTE Operating Bands. Source: 3GPP TS 36.104 V14.3.0 (2017-03). . . 6
2.1 OFDM Modulation Parameters. Source: 3GPP LTE Release 8 . . . 18
4.1 mmWave signals attenuation for different materials [26]. . . 50
4.2 Application scenarios for mmWave networks [81]. . . 53
1G 1st Generation 2G 2nd Generation 3G 3rd Generation
3GPP 3rd Generation Partnership Project 4G 4th Generation
5G 5th Generation
5GPPP 5G Infrastructure Public Private Partnership ADC Analog to Digital Converter
AWGN Additive White Gaussian Noise BER Bit Error Rate
BS Base Station
CDMA Code Division Multiple Access CE-OFDM Constant Envelope OFDM CP Cyclic Prefix
CSI Channel State Information
D-AMPS Digital Advanced Mobile Phone System D-BLAST Diagonal Bell Labs Space-Time Architecture DFT Discrete Fourier Transform
DoF Degree of Freedom
EDGE Enhanced Data Rate for Global Evolution EE Energy Efficiency
EHF Extremely High Frequency FB-OFDM Filter Bank OFDM FDD Frequency Division Duplex
FDMA Frequency Division Multiple Access FFT Fast Fourier Transform
GOFDM Generalized OFDM
GPRS General Packet Radio Service
GSM Global System for Mobile Communications HSCSD High-Speed Circuit Switched Data HSDPA High Speed Downlink Packet Access HSPA High Speed Packet Access
HSUPA High Speed Uplink Packet Access ICI Inter Carrier Interference
IEEE Institute of Electrical and Electronics Engineers IFFT Inverse Fast Fourier Transform
ISI Intersymbol Interference
ITU International Telecommunications Union JDC Japanese Digital Cellular
LMDS Local Multipoint Distribution Service LSAS Large Scale Antenna Systems
LTE Long-Term Evolution mmWave Millimeter Wave
MIMO Multiple-Input Multiple-Output MISO Multiple-Input Single-Output
MU-MIMO Multi-User MIMO
OFDM Orthogonal Frequency Division Multiplexing OFDMA Orthogonal Frequency Division Multiple Access PAPR Peak-to-Average Ratio
QAM Quadrature Amplitude Modulation QoS Quality of Service
QPSK Quadrature Phase Shift Keying RF Radio Frequency
SC-FDMA Single Carrier Frequency Division Multiple Access SE Spectral Efficiency
SFBC Space-frequency Block Code SIMO Single-Input Multiple-Output
SINR Signal-to-Interference-plus-Noise Ratio SISO Single-Input Single-Output
SNR Signal-to-Noise Ratio STBC Space-time Block Code STTC Space-Time Trellis Code SU-MIMO Single-User MIMO SVD Single Value Decomposition TDD Time Division Duplex
TDMA Time Division Multiple Access TSTD Time Shift Transmit Diversity
UMTS Universal Mobile Telecommunications System UT User Terminal
V-BLAST Vertical Bell Labs Space-Time Architecture WCDMA Wideband Code Division Multiple Access WiMAX Worldwide Interoperability for Microwave Access ZFC Zero Forcing Combining
Introduction
This chapter starts by presenting the background and evolution of cellular communications systems, followed by an introduction to the future deployments. This results in a better understanding of the technologies used for the implemented work. Then the motivations, objectives and contributions are identified. Finally, an outline of the document structure is made.
1.1
Background and Evolution of Cellular Communications
Systems
The world’s first mobile phone call was made on April 3, 1973, by Martin Cooper, a Motorola engineer and executive, who placed a call to Dr. Joel S. Engel of Bell Labs. The prototype used by Cooper measured 23 cm long, 13 cm deep, 4.45 cm wide and weighed 1.1 kg. It only offered 30 minutes of conversation and took around 10 hours to re-charge [1]. Obviously, major changes happened since those days, as the perception we nowadays have of mobile phones is completely different than it used to be in the beginning.
In the early 1980s, when mobile phones reached the market, they came with a price tag of around 4000 USD dollars [2], making them a luxury item. Today, it is no longer considered a luxury but more a necessity. This invention allowed people to connect more with each other, making it easier to have a conversation with someone, regardless of distance, and also be an aid in people’s quotidian life.
In general, people who own a mobile phone, use it not only for communications, but for reading the news, checking the time, set the alarm, read a book, see directions, among other examples. It is safe to say that we depend on our mobile phones and they play an important role in our lives. Figure 1.1 shows the evolution of mobile generations and some of its char-acteristics.
1st Generation (1G) systems were implemented in the 1980s, offering basic voice service using analog transmission. There were introduced the Nippon Telephone & Telegraph (NTT) in Japan, Nordic Mobile Telephone (NMT) System in Scandinavian countries, Total Access Communications Systems (TACS) in the UK and Advanced Mobile Phone System (AMPS) in the USA [3]. The spectral efficiency provided was limited, voice quality was poor and there
was no security. Additionally, different countries followed their own standards, which were incompatible between them.
Figure 1.1: Evolution of Mobile Communications.
2nd Generation (2G) systems were deployed in the 1990s. The major difference between 1G and 2G was the transmission technology which upgraded from analog to digital. With this upgrade, voice quality was improved, text messages appeared and the first data services were provided, with speeds of up to 9.6 kbps [4]. Four systems were deployed: Global System for Mobile Communications (GSM) in the European countries; Digital Advanced Mobile Phone System (D-AMPS) IS-54 in the USA; Japanese Digital Cellular (JDC) in Japan and Code Division Multiple Access (CDMA) by Qualcomm, USA [5].
GSM was the standard that gained more popularity, even nowadays, where is currently operating in more than 200 countries. In 2014, its market share was of more than 90 % [6]. The key technologies of GSM are digital transmission and multiple access techniques -Frequency Division Multiple Access (FDMA) and Time Division Multiple Access (TDMA). FDMA divides the available spectrum into several carrier frequencies. Each frequency is then divided using TDMA into several time-slots, allowing simultaneous calls on the same frequency.
The different frequency ranges that GSM operates on are: 900 MHz and 1.8 GHz band in Europe, 850 MHz and 1.9 GHz band in the United States of America and also in Canada and several Latin American countries [6], as seen in table 1.1 below.
Frequency Range (MHz) World Regions
GSM 900 / 1800 Europe, Asia, Australia, Middle East, Africa
GSM 850 / 1900 United States, Canada, Mexico and most countries of S. America
For some time the main focus of cellular systems was to offer voice communication. But simultaneously Internet was having its early growth, so it didn’t took long for network oper-ators to want to include data services into mobile systems. To do so, data packet switching was introduced. GSM works with circuit switching, which consists on establishing a dedicated circuit between two network nodes which remains occupied during the communication session. On the other hand, with packet switching the channel remains busy only when data is transferred, as there is no need for dedicated circuits and therefore complementing the previ-ous technology [7]. General Packet Radio Service (GPRS) adds these elements to the existing GSM network, with average speeds of 40 kbps in the downlink and 14 kbps in the uplink, offering more efficiency and flexibility [8].
The next evolution in the GSM systems was Enhanced Data Rate for Global Evolution (EDGE). This technology uses 8-PSK modulation, conveying 3 bits per symbol and therefore improving data rates by three times [9], which was necessary to support bandwidth extensive data applications. High-Speed Circuit Switched Data (HSCSD) is the service introduced by EDGE that allowed the transmission of more data in each time-slot. Figure 1.2 shows that even in 2017 2G is the generation with more global connections.
Figure 1.2: Global Connections by Technology (in millions) [10].
In 2000, the 3rd Generation (3G) appeared, specified as International Mobile Telecom-munications 2000 (IMT-2000) by the International TelecomTelecom-munications Union (ITU). Some of the requirements for IMT-2000 were: high speed quality; improved spectrum efficiency; high-speed data rates of 2 Mbps indoor, 384 kbps for pedestrian and 144 kbps for vehicular traffic; worldwide common frequency band [11]. In order to accomplish these specifications two concepts were created based on CDMA schemes: Wideband Code Division Multiple Ac-cess (WCDMA) and CDMA 2000 [5].
Universal Mobile Telecommunications System (UMTS) is the result of the standardiza-tion of 3G. Its specificastandardiza-tions provide for both Frequency Division Duplex (FDD) and Time Division Duplex (TDD) variants and includes WCDMA as technique using paired or unpaired 5 MHz channels around a globally agreed bandwidth of 2 GHz [12]. The platform is designed to offer flexibility in data transmission, but also to support different services simultaneously. This means that a user can send and receive data packets while being involved in a voice conversation.
The need to constantly improve data rates led to the appearance of two new technolo-gies: High Speed Downlink Packet Access (HSDPA) and High Speed Uplink Packet Ac-cess (HSUPA), which are known as High Speed Packet AcAc-cess (HSPA) [11].
While 3G is primarily focused on voice, with support for data services, a new technology - Worldwide Interoperability for Microwave Access (WiMAX) - was created with the main focus on broadband data, rather than on voice. Based on the Institute of Electrical and Elec-tronics Engineers (IEEE) standard 802.16, it offered fixed, portable and mobile connectivity, making use of the handover from one base station to another [13]. The WiMAX technology allows wireless connections over a diversity of means between geographically dispersed points, by point to point communication or even with mobile connections, inside of a big coverage area, as seen in figure 1.3.
Long-Term Evolution (LTE) is the standard of what is commonly marketed as 4th Gen-eration (4G). Just as 3G improved upon the speeds of 2G in prior mobile genGen-erations, LTE increases data capacities and transfer speeds of networks, as well as reduces latencies. It first started in 2004, when NTT DoCoMo, a mobile operator of Japan, proposed LTE as an international standard and it was first commercially available in 2009 in Stockholm and Oslo by the Swedish-Finnish mobile network operator TeliaSonera. Since then, LTE expanded worldwide and nowadays almost all network operators offer LTE services [15].
There are two different types of air interfaces used by LTE: one for downlink (from the base station to the terminal), and one for uplink (from the terminal to the base station). For down-link LTE uses Orthogonal Frequency Division Multiple Access (OFDMA), contrary to CDMA and TDMA that have been used for past mobile generations. The OFDMA scheme is also used in standards as IEEE 802.11a/b/g, 802.16, HIPERLAN-2, DVB and DAB [16]. On the other hand, for uplink it uses Single Carrier Frequency Division Multiple Access (SC-FDMA), which in this case is better than OFDMA because it has a lower Peak-to-Average Ratio (PAPR) [17]. Duplex schemes are used both in the downlink and uplink in LTE. Both antennas and devices support the use of duplex schemes in LTE, which can be FDD or TDD and can be used in the two parts even if they use different access schemes.
In the FDD case two channels are used, one for the transmission and the other for recep-tion, which consequently means that are used two different frequencies, while in the TDD case only one frequency is used for the reception and transmission of signals, but are separated in time [18]. Figure 1.4 depicts the differences between both schemes.
Figure 1.4: Differences between FDD and TDD [19].
LTE is defined to support flexible carrier bandwidths from 1.4 MHz up to 20 MHz, in many spectrum bands and for both FDD and TDD deployments. This means that an operator can introduce LTE in both new and existing bands. The FDD and TDD bandwidths defined by 3rd Generation Partnership Project (3GPP) are shown in the table below. Note 1: Band 6, 23 are not applicable. Note 2: Restricted to E-UTRA operation when carrier aggregation is configured. The downlink operating band is paired with the uplink operating band (external) of the carrier aggregation configuration that is supporting the configured Pcell. Note 3: Bands 44, 45, 46, 47, 48, 65, 66, 67, 68, 69 and 70 are not included in this table [21].
E-UTRA
Operating Band Uplink (UL) operating band Downlink (DL) operating band Duplex Mode
1 1920 MHz - 1980 MHz 2110 MHz - 2170 MHz FDD 2 1850 MHz - 1910 MHz 1930 MHz - 1990 MHz FDD 3 1710 MHz - 1785 MHz 1805 MHz - 1880 MHz FDD 4 1710 MHz - 1755 MHz 2110 MHz - 2155 MHz FDD 5 824 MHz - 849 MHz 869 MHz - 894MHz FDD 6 (note 1) 830 MHz - 840 MHz 875 MHz - 885 MHz FDD 7 2500 MHz - 2570 MHz 2620 MHz - 2690 MHz FDD 8 880 MHz - 915 MHz 925 MHz - 960 MHz FDD 9 1749.9 MHz - 1784.9 MHz 1844.9 MHz - 1879.9 MHz FDD 10 1710 MHz - 1770 MHz 2110 MHz - 2170 MHz FDD 11 1427.9 MHz - 1447.9 MHz 1475.9 MHz - 1495.9 MHz FDD 12 699 MHz - 716 MHz 729 MHz - 746 MHz FDD 13 777 MHz - 787 MHz 746 MHz - 756 MHz FDD 14 788 MHz - 798 MHz 758 MHz - 768 MHz FDD 15 Reserved Reserved FDD 16 Reserved Reserved FDD 17 704 MHz - 716 MHz 734 MHz - 746 MHz FDD 18 815 MHz - 830 MHz 860 MHz - 875 MHz FDD 19 830 MHz - 845 MHz 875 MHz - 890 MHz FDD 20 832 MHz - 862 MHz 791 MHz - 821 MHz FDD 21 1447.9 MHz - 1462.9 MHz 1495.9 MHz - 1510.9 MHz FDD 22 3410 MHz - 3490 MHz 3510 MHz - 3590 MHz FDD 23 (note 1) 2000 MHz - 2020 MHz 2180 MHz - 2200 MHz FDD 24 1626.5 MHz - 1660.5 MHz 1525 MHz - 1559 MHz FDD 25 1850 MHz - 1915 MHz 1930 MHz - 1995 MHz FDD 26 814 MHz - 849 MHz 859 MHz - 894 MHz FDD 27 807 MHz - 824 MHz 852 MHz - 869 MHz FDD 28 703 MHz - 748 MHz 758 MHz - 803 MHz FDD 29 N/A 717 MHz - 728 MHz FDD (note 2) 30 2305 MHz - 2315 MHz 2350 MHz - 2360 MHz FDD 31 452.5 MHz - 457.5 MHz 462.5 MHz - 467.5 MHz FDD 32 N/A 1452 MHz - 1496 MHz FDD (note 2) 33 1900 MHz - 1920 MHz 1900 MHz - 1920 MHz TDD 34 2010 MHz - 2025 MHz 2010 MHz - 2025 MHz TDD 35 1850 MHz - 1910 MHz 1850 MHz - 1910 MHz TDD 36 1930 MHz - 1990 MHz 1930 MHz - 1990 MHz TDD 37 1910 MHz - 1930 MHz 1910 MHz - 1930 MHz TDD 38 2570 MHz - 2620 MHz 2570 MHz - 2620 MHz TDD 39 1880 MHz - 1920 MHz 1880 MHz - 1920 MHz TDD 40 2300 MHz - 2400 MHz 2300 MHz - 2400 MHz TDD 41 2496 MHz - 2690 MHz 2496 MHz - 2690 MHz TDD 42 3400 MHz - 3600 MHz 3400 MHz - 3600 MHz TDD 43 3600 MHz - 3800 MHz 3600 MHz - 3800 MHz TDD
Table 1.2: LTE Operating Bands. Source: 3GPP TS 36.104 V14.3.0 (2017-03).
The continuous development of LTE led to the appearance of the LTE-Advanced, which started to be specified in release 10 of the 3rd Generation Partnership Project. On this de-velopment the aimed peak data rates were up to 3 Gbps in the downlink and up to 1.5 Gbps in the uplink. This can be achieved with some enhancements, like carrier aggregation, that increases the bandwidth to 100 MHz, and a higher number of antennas in the base station and mobile terminal [22].
As seen in figure 1.5 below, LTE subscriptions are growing exponentially, having surpassed the 1 billion mark in 2016 and expecting to hit the 3 billion mark by 2019. So far, GSM is still the most used technology, although the paradigm may change by 2020, when LTE will become the most used one. Also by 2020, the next technology - 5th Generation (5G) - is expected to be successfully implemented.
Figure 1.5: LTE subscriptions estimates and forecasts, 2012-2019 (million subscribers). Source: IDATE Digiworld, in State of LTE & MBB spectrum worldwide, December 2015
1.2
5G: The Next Generation
5G is announced for 2020 and even though is far from being standardized, there is a consensus on excepted performance among several regional coordination initiatives: 5G In-frastructure Public Private Partnership (5GPPP) in Europe, 4G Americas in North America,
5GMF in Japan, IMT-2020 (5G) in China and 5G Forum in South Korea, using licensed and unlicensed spectrum above 6 GHz.
5G is the fifth generation mobile networks following 4G and it is designed to interconnect billions of objects, to provide extremely high data rates for multimedia applications and to handle the consequent surging mobile network traffic, which according to CISCO latest Visual Networking Index (VNI) Forecast, will grow 7-fold from 2016 to 2021, reaching 49 Exabytes per month in 2021, up from 7 Exabytes per month in 2016, as illustrated in figure 1.6 [23].
Figure 1.6: Cisco Forecasts 49 Exabytes per Month of Mobile Data Traffic by 2021. Source: Cisco VNI Mobile, 2017
Even though there is not yet standardization, 5G is expected to be more spectrally effi-cient, support many more users, offer higher data rates and provide a more consistent user experience. The 5GPPP is a 1.4 billion EUR collaborative research programme organized as part of the European Commissions Horizon 2020 programmes, the European Union Pro-grammes for Research and Innovation.
5GPPP aims at fostering industry-driven research. Created at the end of 2013, on 17 De-cember, and scheduled to stop in 2020 [24], 5GPPP is currently working on the development of 5G and there are already some key requirements along with some proposed target values like: consistent user experience with bit rates of 0.1 to 1 Gbps depending upon specific use case; peak bit rates of 10 to 50 Gbps; end-to-end latency on the order of 1 to 5 ms or la-tency deviation of 20 s; higher reliability and availability; mobility up to 500 km/hour; wider coverage; device autonomy to enable devices to last days, weeks, months or years without recharging [25]. Figure 1.7 shows the key parameters for 5G.
The current spectrum used for wireless communications, such as AM/FM radio, high-definition TV, cellular, satellite communications, GPS, and Wi-Fi, is saturated. Its range is generally from 300MHz to 3GHz [26]. Therefore, in order to achieve these requirements, changes in the cellular architecture is needed, using new technology, particularly the use of Millimeter Wave (mmWave) communications with massive Multiple-Input Multiple-Output (MIMO).
Figure 1.7: Key Parameters for 5G Mobile Communications [27].
1.3
Motivation and Objectives
Technology is continuously evolving, and nowadays with our smartphone we can not only have voice conversations, but also access the internet, read and send e-mails, watch videos, send and receive multimedia data, use navigation services, among others. In order to cope with these developments, there is a need for more data applications, faster speeds, more ca-pacity, less latency and in general, a better performance. New cellular architectures need to be created in order to handle the increasing demand for wireless services.
Massive MIMO and mmWave are two technologies that are expected to be an important factor in the development of the next generation, 5G. They are considered to be two of the key enabling technologies needed to meet the Quality of Service (QoS) requirements for fu-ture wireless communications [28]. Conjugating these two technologies allows putting a higher number of antennas into the same volume, since mmWave have a smaller wavelength than the currently used cellular systems. Consequently, both terminals can be equipped with a higher number of antennas, which serves enough antenna gains to compensate the attenuation from higher frequencies.
However, full digital transmission and/or receiving beamforming techniques for massive MIMO require a fully dedicated Radio Frequency (RF) chain for each antenna. This leads to higher costs and power consumption due to the hardware complexity. Another significant issue is the mmWave propagation characteristics, since there are specific zones with reason-able attenuation, which does not happen in lower frequencies [26].
phase shifters. However, practical analog beam-formers employ only a quantized number of phase shifts and their constraints on the amplitudes, which constitutes a limitation on the performance of the system [29]. Consequently, new analysis and studies have been developed with new transceiver structures, in order to overcome the limitations described above. An important alternative is the use of hybrid analog and digital beamforming structures, where the signal processing is made in both analog and digital domains [30][31].
The objective of this dissertation is to design and evaluate a hybrid linear multi-user equal-izer for broadband mmWave massive MIMO SC-FDMA systems. We consider low-complexity single antenna SC-FDMA user terminals and at the receiver side, we design an efficient hybrid multi-user equalizer by minimizing the average Bit Error Rate (BER) of all subcarriers. We assume that the analog part is constant over all subcarriers while the digital part is computed on a per subcarrier basis. Due to the complexity of the optimization problem we propose an iterative approach to sequentially compute the analog phase shifter for each RF chain. The implemented scheme is evaluated under mmWave realistic channel models. The simulation results show that the proposed hybrid equalizer achieves an average BER close to the full-digital equalizer (gap of ∼ 1 dB), when the number of RF chains is twice the number of users. When the number of RF chains is smaller than twice the number of users, a compromise between complexity and performance is achieved.
1.4
Contributions
The main contribution of this dissertation was the development of a new hybrid multi-user linear equalizer for broadband mmWave massive MIMO systems, which originated the following article
• G. Barb, D. Castanheira, G. Anjos, A. Silva and A. Gameiro, ”A New Hybrid Multi-User Linear Equalizer Scheme for Broadband Millimeter Wave Systems”, submitted to IEEE Access, June 2017.
1.5
Outline
This dissertation started with the introduction on the background and evolution of cellular communications systems, followed by the motivation and objectives. The remaining chapters are organized as follows,
In chapter 2, multiple access techniques in cellular networks are presented. The OFDMA and SC-FDMA systems are studied, in particular their characteristics such as modulation, orthogonality and the introduction of a cyclic prefix to avoid interference. A comparison between both systems is made. Additionally, new modulation techniques envisioned for the future wireless communications systems are described.
In chapter 3, we present the main characteristics of multiple antenna systems, such as diversity, spatial multiplexing, as well as their advantages and enabling techniques. Lastly, the use of massive MIMO is studied, were is detailed its potential, challenges and advantages
and disadvantages.
Following, in chapter 4, we describe the millimeter waves systems, its characteristics, ap-plications and advantages and disadvantages. Following is the use of millimeter waves with massive MIMO systems, as a promising technique for the future mobile generations. Finally, some advanced architectures are presented.
In chapter 5, the implemented receive beamforming scheme for millimeter waves with massive MIMO is described. Starting with the system characterization, the transmitted and receiver model and lastly the equalization scheme. Later, the proposed solution is evaluated under a realistic mmWave channel model.
The last chapter, chapter 6, finalizes this dissertation with the work conclusions and future possible research guidelines.
1.6
List of Notations
The following notation is used in this dissertation: boldface uppercase letters, boldface lowercase letters and italic lowercase letters denote matrices, vectors and scalars, respectively. The operations (.)T, (.)H, (.)∗and tr(.) represent the transpose, the Hermitian transpose, the conjugate and the trace of a matrix,respectively. Consider a matrix A , diag(A) corresponds to a diagonal matrix with entries equal to the diagonal entries of the matrix A. The indices t, k and u represent the time domain, subcarrier in frequency domain and user terminal, respectively. IN is the identity matrix of size N ×N . E[.] represents the expectation operator. {αl}Ll=1 represents an L length sequence.
Single and Multicarrier Systems
There are different techniques and schemes used for the transmission of information in communications systems, with the purpose to achieve the goals of the respective system. For that reason, and to permit an efficient recovery of the received data signal, modulation tech-niques represent an important part of the transmission as well as equalization techtech-niques of the received data signal.
In a single carrier transmission, the data signal is modulated in phase, amplitude or fre-quency by one single carrier. Consequently, this leads to some limitations, such as: achieving high data rates implies a high symbol rate and thus high bandwidth, and also the tendency of mobile radio channels to be dispersive and time-variant. As the radio spectrum is a limited resource and is becoming more and more saturated, efficiency is an essential factor when designing a new system. In order to combine the high data rates with spectral efficiency, the use of multicarrier systems becomes a natural solution [32].
In a multicarrier transmission, the data signal is divided into several different sub-streams that are sent via different sub-channels. Hence, due to the division of the data rate of the signal, the data rate of each sub-channel is lower than the total data rate. This way, also the bandwidth of each sub-channel is smaller than the total system bandwidth.
This chapter focuses on single and multicarrier systems, namely OFDMA and SC-FDMA. Their characteristics are presented, such as modulation, orthogonality and cyclic prefix addi-tion. Also the detection techniques used in SC-FDMA are presented. A comparison between both these systems is presented. Formerly, new modulation techniques being studied for the future wireless communications systems are introduced.
2.1
Orthogonal Frequency Division Multiplexing
Orthogonal Frequency Division Multiplexing (OFDM) is a modulation form part of the multicarrier systems. The basic principle of OFDM is to divide a high rate data stream into a number of lower rate data streams that are simultaneously transmitted over a number of parallel subcarriers [33]. Figure 2.1 shows the conversion of one high data stream into a number of lower rate data streams.
Figure 2.1: OFDM modulation with Ncsubcarriers.
2.1.1 Modulation
In an OFDM modulation with Nc subcarriers and B total bandwidth, dk parallel data symbols are transmitted, each one modulated in one different subcarrier, where k =0,..., Nc-1. The spacing between subcarriers is
∆fc= B Nc
(2.1) The OFDM symbol duration in a subcarrier is given by
T = 1 ∆fc
(2.2) Since each symbol occupies a narrowband with a longer time period, the delay spread has a lower Intersymbol Interference (ISI) on the received data symbols. Thus, it is reasonable to say that the multicarrier approach converts the channel into a flat fading one, making it easy to be estimated [34]. This is one of the advantages of using OFDM, because the increasing of the symbol period makes the delay spread being a significantly shorter fraction of the symbol period, resulting in a channel that is less sensitive to fading, noise, channel distortion and ISI. The Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (IFFT) are two mathematical tools used in the receiver and transmitter part of the OFDM, respectively. These tools enable us to move back and forth between time and frequency domains without losing information. The received signal is
r(t) = Re (Nc−1 X k=0 dkrect (t/T ) ej2πkt/Tej2πtfc ) (2.3) So, the received signal after removing the RF carrier, for a time slot of duration T, is
s(t) = r(t)e−j2πfct=
Nc−1
X k=0
If we sample the sequence at a rate Nc/T , we get the set of Ncsamples s(n) = s(nT /Nc) = Nc−1 X k=0 dkej2πkn/Nc, n = 0, 1, ..., Nc− 1 (2.5) This is [sn] = IF F T [dk] =⇒ [dk] = F F T [sn], (2.6) Therefore, the original sequence dk can be recovered by sampling it at a rate Nc/T , and applying the FFT over the Ncsamples from one slot with duration T [17] [35].
2.1.2 Orthogonality
Orthogonality is an important characteristic of OFDM since it makes it possible to overlap different subcarriers without suffering from Inter Carrier Interference (ICI), and consequently increase the spectral efficiency [34]. In the frequency domain, each subcarrier translates in a sinc function with side lobes, provoking overlapping and causing ICI. But if the frequencies are orthogonal, when one reaches its peak the others reach their nulls. Therefore, there is no interference and the system can recover the original signal without any problems [36].
The fundamental condition of orthogonality is expressed in the following equation T Z 0 Si(t).Sj(t) = A i = j 0 i 6= j (2.7)
If we observe figure 2.2, we can see the overlapping of the different subcarriers, but when one reaches its peak, the others are null, confirming the orthogonality between subcarriers.
2.1.3 Cyclic Prefix
When OFDM subcarriers pass through a time-dispersive channel, they can lose their orthogonality and cause ISI. The solution passes by introducing a Cyclic Prefix (CP). This is, copying the last part of a symbol and attaching it to the beginning of it, extending the length of the symbol. The extended OFDM symbol has now the duration of
T0 = TCP + T, (2.8)
where T is the initial symbol duration, TCP the added cyclic prefix and T
0
the resulting symbol duration. See figure 2.3 below.
Figure 2.3: Cyclic Prefix.
Therefore, in order to fully remove the ISI and maintain the orthogonality between sub-carriers, the duration of the cyclic prefix needs to be higher than the maximum delay spread of the multipath channel
TCP > τmax (2.9)
The consequence is a loss in spectral efficiency, since the transmission rate is reduced. Also, in order to fully remove the ICI, the subcarrier spacing, ∆fc, needs to be two times higher than the maximum Doppler shift, fD
∆fc 2fD,max (2.10)
So, the CP length needs to be chosen very carefully. For LTE, the standard length is 4.67 µs for short CP and 16.67 µs for long CP. The Signal-to-Noise Ratio (SNR) loss due to the addition of the CP is expressed in the following equation
SN Rloss= Psignal Pnoise = T 0 T0− TCP (2.11)
The spectral efficiency can be expressed as
η = SN Rloss−1 (2.12)
Therefore, for the OFDM symbol period of 66.67 µs (as specified in LTE), the system has a performance of 93.5% with short CP and 80% with long CP.
Short CP SN Rloss= 4.67+66.67−4.674.67+66.67 = 1.07005 η = SN R−1loss= 1.070051 = 0.935 Long CP SN Rloss= 16.67+66.67−16.6716.67+66.67 = 1.25004 η = SN R−1loss= 1.250041 = 0.8 (2.13) 2.1.4 OFDM Architecture
Figure 2.4 depicts the general OFDM transmitter and receiver block diagram. Firstly, the bits stream is modulated into symbols, using Quadrature Amplitude Modulation (QAM) or Quadrature Phase Shift Keying (QPSK) modulation, for example. Then, the IFFT is applied, defining the signal in time domain. Finally the cyclic prefix is added to ensure orthogonality by fully removing the ISI, as discussed before [32].
At the receiver, the first step is to remove the cyclic prefix added in the transmission part. After the removal, FFT is applied to convert the signal into frequency domain and an equalizer is applied to remove the channel effects. Lastly, the data symbols are demodulated to obtain the original bits stream [32].
OFDM is used in a number of systems such as WiMAX and LTE. Table 2.1 below depicts the specifications of OFDM used in LTE.
Transmission Bandwidth (MHz) 1.4 3 5 10 15 20 Sampling Frequency (MHz) 1.92 3.84 7.68 15.36 23.04 30.72 IFFT(Tx) / FFT(Rx) size 128 256 512 1024 1536 2048 Number of Occupied Subcarriers 72 180 300 600 900 1200 Subcarrier Period (s) 66.67 s Slot Duration (ms) 0.5 ms Subcarrier Spacing (kHz) 15 kHz
Number of OFDM Symbols per Slot
(short/long CP) 7 symbols (short CP) or 6 symbols (long CP) Cyclic Prefix Length
Short CP 4.67 s
Cyclic Prefix Length
Long CP 16.67 s
Table 2.1: OFDM Modulation Parameters. Source: 3GPP LTE Release 8
If we consider the 1.4 MHz bandwidth, the sampling frequency is 1.92 MHz and the FFT size 128. This means that, within the 66.67 µs FFT period, there are 128 samples. Either short or long CP is used taking in account the channel delay spread, as explained before. If short CP is used, we have 7 OFDM symbols per slot with a CP duration of 4.67µs. Also (7 × 66.67 + 7 × 4.67) ≈ 0.5 ms, which is the slot duration. On the other hand, if long CP is used, we have 6 OFDM symbols per slot with a CP duration of 16.67µs.
2.2
OFDMA System
OFDMA is a multiple access technique, which can be translated as an extension of OFDM to the implementation of a multi-user communications system. Figure 2.5 depicts the differ-ences between OFDM and OFDMA. In OFDM, the subcarriers allocated of a single-user are fixed for transmitting the data symbols. In OFDMA, all subcarriers can be shared with multiple users and the allocation is dynamic. This is, OFDMA distributes different sets of subcarriers to different users at the same time.
Figure 2.5: OFDM and OFDMA comparison.
The ability to distribute the numbers of subcarriers to the users demonstrates the flexi-bility of OFDMA systems. Figure 2.6 shows the different subcarrier mapping types. If the subcarriers of one user are allocated in an adjacent way, and therefore for several users in contiguous groups, the type of mapping is named localized. On the other hand, if the alloca-tion is done arbitrarily for the different users, then the type of mapping is named distributed [38].
Figure 2.6: Types of subcarriers mapping [17].
The advantages of OFDMA are: an efficient use of spectrum, due to the flexibility of the system; frequency diversity due to the possibility of spreading the subcarriers all over the used spectrum; possibility of minimizing the interference from adjacent cells by using differ-ent subcarriers permutation between the respective cells; allocating the resources having in account the needs of the transmitted signal reducing the impact regarding time and frequency fading, and therefore requiring simple equalization techniques in frequency domain [39][40].
On the contrary, there are also disadvantages of OFDMA, such as: non-constant envelop of the modulated signal which reduces the efficiency of the RF power amplifier, leading to
high PAPR; susceptibility to synchronization errors due to the small spacing of the subcarri-ers [39][40].
OFDMA is used in the downlink of LTE, but due to its high PAPR it can not be used in the uplink. Therefore, for the uplink the multiple access technique that is used is SC-FDMA.
2.3
SC-FDMA System
SC-FDMA is a multiple access technique that is used in the uplink of LTE. Its structure is similar to OFDMA. For the transmitter, the constellation mapping performs the modulation of bits into symbols blocks. The modulation schemes defined for LTE are QPSK, 16-QAM and 64-QAM [41]. Then, it performs a S -Point FFT for a set of S data symbols, to convert the symbols blocks into frequency domain.
The S -Point FFT size in LTE is restricted to products of the integers two, three and five. It is important to notice that the uplink resource attribution is always performed with blocks of size 12 subcarriers, so the S -point FFT size has the particularity of always being a multiple of 12 and
S = 12 × 2a23a35a5 (2.14)
Following is the subcarrier mapping, where it maps the output blocks to the Nc subcarri-ers. The Nc-Point IFFT, as in OFDMA, converts the subcarrier amplitudes to time domain. Lastly, the cyclic prefix is added to the signal before being transmitted, similar to OFDMA [42].
Figure 2.7: SC-FDMA Transmitter Block Diagram [17].
For the receiver, the Nc-Point FFT is applied to convert the signal to frequency domain, as in OFDMA. After, subcarriers are de-mapped and equalization is performed in the frequency
domain. There are several methods of equalization which are going to be explained after. Then, the equalized symbol blocks are converted to time domain through S -Point IFFT. Fi-nally, the symbols are demodulated so the original signal is recovered [42].
Figure 2.8: SC-FDMA Receiver Block Diagram [17].
2.3.1 Equalization Schemes used in SC-FDMA
The single-user frequency domain equalizers used in SC-FDMA systems with Nc channel coefficients are
• Maximum Ratio Combining (MRC):
gl= h∗l , l = 1, ..., Nc (2.15) The MRC equalization intention is to maximize the instantaneous SNR at the receiver. This method presents good results for an Additive White Gaussian Noise (AWGN) channel, since the signal is multiplied by a weight factor that is proportional to the sig-nal amplitude. Therefore, branches with strong sigsig-nals are further amplified than weak signals, that are attenuated. The equalizer coefficients are acquired from the complex conjugate of the frequency response of the channel h [46].
• Equal Gain Combining (EGC):
gl= h∗l |h∗ l|
, l = 1, ..., Nc (2.16)
The EGC technique is less complex, and subsequently only needs the phase information of the channel coefficients. Phase equalization can be executed at the transmitter in
form of EGC, so that all subcarriers reach the receiver in phase. This design compen-sates only the phase rotation by the channel, and does not tries to equalize the effects of amplitude scaling introduced by different channel attenuations at different subcarrier frequencies [46].
• Zero Forcing Combining (ZFC):
gl= h∗l
|h∗l|2 , l = 1, ..., Nc (2.17) The ZFC equalizer recovers the orthogonality between distinct users, pushing the ISI to zero. Although a great inconvenience of the ZFC equalizer is that it amplifies noise especially for the channel coefficients with low amplitude. The coefficients can be ac-quired merely by flipping the channel [46].
• Minimum Mean Square Error Combining (MMSEC):
gl= h∗l
|h∗l|2+ σ2 , l = 1, ..., Nc, (2.18) where σ2 is the noise variance. The MMSEC procedure is optimal when we consider a channel with noise and interference. It is easy to verify that when σ ⇒ 0 the MMSEC equalizer is identical to the ZFC. The coefficients are found by minimizing the mean square error between the transmitted signal before modulation and signal to the equal-izer on each subcarrier [46].
2.4
OFDMA and SC-FDMA Systems Comparison
OFDMA and SC-FDMA are two multiple access techniques detailed in the previous sec-tions. Using figure 2.9 as an example, we can observe that the sequence to be transmitted is composed by 4 QPSK data symbols.
For the OFDMA, each symbol period transmits 4 QPSK data symbols in parallel, one symbol per subcarrier. For the SC-FDMA, each symbol period also transmits 4 QPSK data symbols, but now spread over the 4 subcarriers. Therefore, each SC-FDMA symbol occupies 4 × 15 kHz bandwidth.
The parallel transmission of data symbols leads to the high PAPR in OFDMA. This does not happen in the SC-FDMA case even if the bandwidth is the same as OFDMA, since the PAPR is equal as that used for the original data symbols [44].
For the SC-FDMA case, frequency diversity can be achieved since the data is spreaded out through the bandwidth and therefore 4 copies of the same data are transmitted, which does not happen in the OFDM case.
Figure 2.9: Comparison between OFDMA and SC-FDMA [43].
2.5
Modulation Techniques for the Future Wireless
Commu-nications Systems
As seen above, LTE uses SC-FDMA as multiple access technique for uplink and OFDMA for downlink. New modulation techniques are being exploited for the future wireless commu-nications systems.
2.5.1 Constant Envelope OFDM
OFDM is widely used as a modulation technique for transmitting signals in digital com-munications. However, one of the main disadvantages is, as seen before, the high PAPR which diminishes the efficiency of power amplifiers, therefore increasing the complexity in order to overcome the problem.
So far, there have been many techniques exploited to address the PAPR issues: distortion-less PAPR reduction schemes such as coding and tone reservation, non-distortiondistortion-less PAPR reduction schemes such as clipping/filtering and peak windowing, and predistortion schemes. These schemes provide different levels of efficiency, although presenting trade-offs with in-creased complexity, performance degradation or reduced spectral efficiency [47].
Constant Envelope OFDM (CE-OFDM) is a promising modulation technique for the fu-ture wireless systems that provides a solution for the high PAPR in OFDM.
A constant envelope waveform is a type of waveform where the envelope of the carrier is constant, regardless of the variation in the modulating signal. The baseband form of a constant envelope signal is given by
s(t) = Aejθ(t), (2.19)
where A is the signal’s amplitude and θ(t) is the phase signal [48]. The instantaneous power is a constant |s(t)|2 = A2. The OFDM with constant envelope is what defines the modulation technique CE-OFDM.
In order to obtain CE-OFDM, the OFDM signal is separated into real and imaginary parts and a phase modulator is added to both the transmitter and receiver. This leads to the CE-OFDM bandpass signal to have constant envelope bandpass signal. Figure 2.10 depicts the differences of the bandpass signal of OFDM and CE-OFDM. It also shows the differences of an OFDM lowpass signal and the CE-OFDM one.
Figure 2.10: CE-OFDM and OFDM envelope comparison [48].
The instantaneous signal power of a CE-OFDM system is always constant, therefore when calculating the PAPR, the peak power and the average power will be equal, leading to a PAPR of 0 dB. Figure 2.11 compares the instantaneous power of an OFDM signal with a CE-OFDM.
We can observe that the high PAPR signal of OFDM is transformed into a constant en-velop signal, i.e., with 0 dB PAPR [49].
Since the high PAPR is a problem due to its needs of highly efficient, linear power am-plifiers and the reduced power efficiency, CE-OFDM completely erases the need for linear amplifiers, providing a significant increase in power efficiency of OFDM systems.
Figure 2.11: Instantaneous power of OFDM and CE-OFDM systems [48].
CE-OFDM is particularly interesting for the future mmWave based communications, since the high PAPR is no longer a problem and consequently it allows highly efficient power ampli-fication by using nonlinear amplifiers. Nevertheless, CE-OFDM requires a higher bandwidth than conventional OFDM systems.
2.5.2 Filter Bank OFDM
Filter Bank OFDM (FB-OFDM) is a modulation technique that is also being investigated for the future wireless communications systems. The idea is to combine OFDM with filter bank, as the name states, dividing the input signal into a set of analysis signals. Therefore, the concept is to extend the QAM symbols to an extended symbol basis, according to a pre-defined symbol extension pattern. After the symbol extension, the symbols are mapped to an extended sub-channel band.
The objective is to find a proper symbol extension pattern, such that the transmitter symbols can be perfectly recovered at the receiver. Figure 2.12 depicts the FB-OFDM block diagram at both the transmitter and receiver [51].
Figure 2.12: FB-OFDM modulation and demodulation diagram [51].
At the transmitter, there are four main steps for the modulation. Firstly, the blocks of QAM symbols, s ∈ CNc×K, are extended according to a predefined symbol extension
pat-tern to sE∈ CNc×2K−1, where N
cis the number of subcarriers and K the extension factor [52]. Following is the filtering and mapping processes. The output from these two processes, a so-called combinational symbol vector, denoted by c ∈ CNcK×1, can be expressed as
c = Nc−1
X n=0
cn (2.20)
Lastly, the combinational symbols are transformed from frequency to time domain via NcK -point IFFT. The output of the FB-OFDM signal, y ∈ CNcK×1, is given by
y = FHc, (2.21)
where F ∈ CNcK×NcK is the normalized DFT matrix.
The demodulation process at the receiver is quite similar to the modulation, as seen in figure 2.12. Firstly, the received signal is transformed from time to frequency domain via NcK -point FFT, resulting in the signal ˆc ∈ CNcK×1
ˆ
c = Fy (2.22)
Following is the demapping and filtering processes. Lastly is the symbol recovery block, from which the symbols are successfully recovered.
In conclusion, FB-OFDM is a modulation scheme completely compatible to OFDM, due to their similarity. However, the arithmetical computation complexity in FB-OFDM is 30% higher than in OFDM. Also, due to its compatibility, complementary techniques such as channel estimation, equalization, MIMO precoding and decoding can be straightforwardly re-used for FB-OFDM without the needs of additional re-design efforts [51].
2.5.3 GOFDM
Generalized OFDM (GOFDM) is a modulation technique also introduced in order to over-come the high PAPR of OFDM systems. In GOFDM, several OFDM symbols with a reduced number of subcarriers are time-multiplexed in the GOFDM frame during the time window of the FFT in OFDM. This way, the transmission data rate is kept the same [53].
If the number of subcarriers is reduced to one, GOFDM becomes single-carrier and if it is equal to the FFT window size, then becomes conventional OFDM. Therefore, we can say that GOFDM bridges OFDM and single-carrier transmission.
Figure 2.13: GOFDM transmitter and receiver block diagram.
The transmitter/receiver block diagram of the GOFDM system is presented in figure 2.13. At the transmitter, the Nc bit stream is modulated and then divided into P data blocks of size Ns=Nc/P. A short Ns-point IFFT spreading is applied to each of these blocks. One frame of GOFDM signal with Ncsamples is composed by the sequence of P OFDM signals. Lastly, as in OFDM, a CP is added.
For the receiver side, the CP is firstly removed from the received signal, then a short Nc-point FFT de-spreading is performed, proceeded by a frequency domain equalizer. The resulting components are transformed back into time domain by applying Nc-point IFFT. Then, the signal is divided into P data blocks, followed by Ns-point FFT applied to each block. Lastly, the data is demodulated.
When compared with the conventional OFDM system, the PAPR of GOFDM is reduced by a factor of P=Nc/Ns. To note that for the OFDM system, one frame has one OFDM symbol with Nc subcarriers, this is, P =1 [54].
In conclusion, to overcome the high PAPR of conventional OFDM systems, multiple OFDM symbols with reduced number of subcarriers are time-multiplexed in the GOFDM frame during the FFT time window. In terms of BER, GOFDM achieves a better BER per-formance than OFDM. If the channel has more frequency selectivity, then a larger frequency diversity effect is obtained and the BER performance is improved.
Multiple Antenna Systems
Wireless communications are continuously evolving and the demand for higher data rates, more capacity, a better QoS and more coverage is rising. The use of multiple antenna systems meets these requirements without consuming additional bandwidth or power [55]. Also, these systems brought the opportunity to exploit spatial dimension by creating different paths be-tween the transmitter and receiver [56].
This chapter focuses on multiple antenna systems. It starts by presenting the different antenna configurations, followed by the diversity techniques. After, spatial multiplexing tech-niques are explained. Lastly, the use of massive MIMO is detailed.
3.1
Antenna Configurations
There are three multi-antenna possible formats. They differ on the number of anten-nas used at the transmitter and receiver and are: Single-Input Multiple-Output (SIMO), Multiple-Input Single-Output (MISO) and MIMO. To begin and for comparison reasons, we start by presenting the Single-Input Single-Output (SISO) configuration, which is the less complex one, with only one transmit antenna and one receive antenna. There is no diversity in this case, since there is only one possible path.
The SIMO configuration is defined by having one transmit antenna and two or more receive antennas, as shown in figure 3.1. This scheme describes receive diversity, since the receiving signals can arrive from different independent paths. This leads to higher processing techniques at the receiver side.
The MISO configuration uses two or more transmit antennas and only one receive antenna. This scheme describes transmit diversity, since the data signal is transmitted redundantly by different antennas. When compared with the previous scheme, this one presents the advan-tage of the complexity change, which is now on the transmitter side, allowing the receiver to reconstruct the original data stream from the best signal received, without complex process-ing techniques.
Lastly, there is the MIMO configuration, which is defined by having multiple antennas on the transmitter side and receiver. By transmitting multiple data streams simultaneously in frequency and time, the spectral efficiency is increased and channel robustness is provided. This is called spatial multiplexing. This configuration has more hardware complexity attached to it, since each antenna needs a RF unit. In addition, the processing algorithms are more complex, which leads to more power consumption [58].
Figure 3.1: Antenna Configurations [57].
3.2
Diversity
Diversity is the principle adopted by multiple antenna systems. This is, sending the same information through different independent paths [17]. The idea is to combine the different paths in order to mitigate the fading effects, since multiple independent paths are unlikely to fade simultaneously. Thus, the probability of noise and attenuation is reduced [59]. There are three main different ways to apply diversity, and they are
Time Diversity:
more than the coherence time. Time interleaving and channel coding is used in practice. The code provides redundancy and the interleaving guarantees that the bits associated with a codeword are time separated enough to undergo different channel fading. The main drawback is the decrease of the data rate by L with repetition code, where L is the number of the different independent paths. Figure 3.2 shows an example, where t, f and s represent the time, frequency and space axis, respectively.
Figure 3.2: Time diversity [5].
Frequency Diversity:
The same narrowband signal is transmitted at different carriers, where the carriers are separated by the coherence bandwidth of the channel. The main drawback is that it usually requires more bandwidth. Figure 3.3 depicts frequency diversity, where again t, f and s represent the time, frequency and space axis, respectively.
Figure 3.3: Frequency diversity [5].
Spatial/Antenna Diversity:
The same information is transmitted via different antennas spatially separated. Unlike time and frequency diversity, spatial diversity does not need to increase the bandwidth and transmitted power, which raises the interest of its use for cellular communications [60].
3.2.1 Receive Diversity
Receive diversity is an effective technique used to mitigate fading and multipath distor-tions. It combines the signals received, allowing the antennas to filter the multipath fading in different ways. Furthermore, if one antenna is experiencing deep fading, it is unlikely that another one is also experiencing. Figure 3.4 shows the resulting signal at the receiver, which is a combination of two signals from two antennas.
Figure 3.4: Receive Diversity System [62].
So, the quality of the received signal depends on how the multiple replicas of the signal are combined, in order to improve the SNR. Receive diversity can achieve both diversity gain and antenna gain. The diversity gain is related to the fact that the channels are independent and the antenna gain is related to the fact that the noise terms added at each receiver are independent [17]. Therefore, different ways of combining the multiple replicas of the signal are
• Maximal Ratio Combining, where each received signal is individually co-phased and weighted on their SNR before adding them all.
• Equal Gain Combining, where the signals are co-phased on each branch and later on summed with equal gain.
• Selection Combining, where a selection algorithm compares the instantaneous ampli-tude of each channel, choosing the antenna branch with the highest ampliampli-tude. More-over, the remaining signals from others antennas are ignored.
• Switched Combining, where the receiver switches to another signal when the current one selected drops below a predefined value.
3.2.2 Transmit Diversity
Transmit diversity is defined by using two or more antennas on the transmitter side. For this case, there is the need of adding coding/precoding techniques, otherwise the signal would be transmitted through the multiple antennas and when would reach the receiver side, the signals would simply be added together, which could cause destructive interference and not achieving diversity. Further, transmit diversity is specially interesting for the downlink, since it is easier to install multiple antennas at the base station, contrary to the mobile terminal.
There are two ways of achieving transmit diversity: closed loop transmit diversity and open loop transmit diversity [17].
Closed Loop
The closed loop transmit diversity takes in account the Channel State Information (CSI), which is the known channel properties of the communication link. Therefore, before sending the signal over all transmit antennas, a phase shift is applied by the transmitter, so all the replicas of the signal are in phase when arriving at the receiver, avoiding the destructive interference.
There are two ways to know the channel before transmission. The first one is acquiring the information in the uplink by the base station, being appropriate when considering TDD systems, since there is channel reciprocity. The second one is by obtaining that information by feedback from the mobile terminal, being appropriate if considering FDD. For both cases, the channel variations must be sufficiently slow in order to avoid substantial variations be-tween the instant of acquisition and the usage of the channel.
Open Loop
The open loop transmit diversity uses space-time/frequency codification. Contrary to closed loop transmit diversity, open loop techniques do not require CSI, offering robustness against non-ideal conditions, such as antenna correlation and channel estimation errors.
There are predominantly two types of space-time/frequency codes: Space-Time Trellis Code (STTC) and space-time/frequency block coding. Trellis code requires more complexity and therefore its use in practical systems is limited, although it typically outperforms the block codes. Space-time Block Code (STBC) and Space-frequency Block Code (SFBC) are the two types of block coding [17] [64].
Figure 3.5 depicts the Alamouti’s block diagram for the open loop transmit diversity. Firstly, the bits are modulated using an M -ary modulation, for example QAM, and then converted into symbols, s1 and s2, which are coded in two antennas. The transmitted signal matrix, where s1 and s2 are transmitted in the first time slot by antenna 1 and 2 and -s∗2 and s∗1 are transmitted in the second time slot also by antenna 1 and 2, is
S = s1 −s∗2 s2 s∗1 (3.1)
Figure 3.5: Alamouti scheme with 2 transmit antennas and 1 receive antenna - encoder [17]. The code used on antenna 1 is orthogonal to the one used on antenna 2, and therefore s1 and s2 are independent. This can be proven by performing the following operation
S × SH = |s1|2+ |s2|2 0 0 |s1|2+ |s2|2 (3.2) Figure 3.6 depicts the block diagram of the Alamouti space-time decoder.
Figure 3.6: Alamouti scheme with 2 transmit antennas and 1 receive antenna - decoder [17]. Consider now the scheme and the Alamouti code presented in figure 3.7 below.
Figure 3.7: Alamouti scheme and code [17].
The received signals at time/frequency n and n+1, where each symbol is multiplied by a factor of √1
2 in order to normalize the power per symbol, are given by yn= 1 √ 2h1,nsn+ 1 √ 2h2,nsn+1+ nn yn+1= − 1 √ 2h1,n+1s ∗ n+1+ 1 √ 2h2,n+1s ∗ n+ nn+1 (3.3)
