Implementation and performance evaluation of MIMO GFDM systems

(1)

Universidade de Aveiro Departamento de Eletrónica, Telecomunicações e Informática 2020

Joumana

Kassam

Implementação e avaliação do desempenho de

sistemas MIMO GFDM

(2)

(3)

“ Success is not final, failure is not fatal: it is the courage to con-Universidade de Aveiro Departamento de Eletrónica, Telecomunicações e Informática 2020

Joumana

Kassam

Implementação e avaliação do desempenho de

sistemas MIMO GFDM

Implementation and performance evaluation of

MIMO GFDM systems

(4)

(5)

Universidade de Aveiro Departamento de Eletrónica, Telecomunicações e Informática 2020

Joumana

Kassam

Implementação e avaliação do desempenho de

sistemas MIMO GFDM

Implementation and performance evaluation of

MIMO GFDM systems

Dissertação apresentada à Universidade de Aveiro para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Engenharia Elec-trónica e Telecomunicações, realizada sob a orientação científica do Doutor Professor Adão Silva, Professor Auxiliar da Universidade de Aveiro do Depar-tamento de Eletrónica, Telecomunicações e Informática da Universidade de Aveiro, e do Doutor Daniel Castanheira, investigador auxiliar no Instituto de Telecomunicações pólo de Aveiro.

This work is supported by the European Regional Development Fund (FEDER), through the Competitiveness and Internationalization Operational Program (COMPETE 2020) of the Portugal 2020 framework, Regional OP Centro (CENTRO 2020), Regional OP Lisboa (LISBOA 14-20) and by FCT/MEC through national funds, under Project MASSIVE5G (AAC no 02/SAICT/2017).

(6)

(7)

o júri / the jury

presidente / president Professor Doutor António Luís Jesus Teixeira

Professor Associado C/ Agregação, Universidade de Aveiro

vogais / examiners committee Professor Doutor Rui Miguel Henriques Dias Morgado Dinis

(8)

(9)

agradecimentos / acknowledgements

First of all, I would like to thank my supervisor Professor Adão Silva and my co-supervisor Doctor Daniel Castanheira for their continuous support, help, exceptional supervision, mentoring, and review of my thesis document with their expert opinions.

I would like to thank the Global Platform for Syrian Students represented by former President Jorge Sampaio and his Diplomatic Adviser Dr. Helena Barroco. I am really grateful to the Portuguese for the enormous opportunity that was given to me for achieving my goal by proceeding the higher studies.

My heartiest gratitude goes to my husband and all my family for their love, trust, affection, patience, and support throughout this study period. I am also grateful to all my friends and my colleagues in IT for providing assistance and a friendly working environment.

Last but not least, thank you very much to the University of Aveiro, the Department of Electronics, Telecommunications, and Informatics and the

(10)

(11)

Palavras Chave 5G, Além 5G, Esquemas de modelação, GFDM, MIMO, Técnicas de cancela-mento de interferência.

Resumo A tecnologia OFDM é utilizada nos sistemas de telecomunicações 4G e será também nos sistemas 5G. Apesar das suas características e resultados, é possível melhorar a sua performance em termos de eficiência espectral. GFDM é um novo conceito de modulação digital de multiportadora não ortogonal. Esta tem como objetivos alcançar uma maior eficiência espectral, um melhor controlo de emissões OOB(emissões fora da banda), devido à sua flexibilidade para escolher um filtro de modelação de pulso, e ainda reduzir o PAPR comparativamente ao OFDM. A eficiência espectral em redes sem fios pode ainda ser melhorada através do uso da tecnologia MIMO, tendo sido adotada em vários sistemas comerciais. Assim sendo, a combinação da tecnologia MIMO com a modulação GFDM permite melhorar considera-velmente o desempenho dos sistemas, já que melhora a eficiência espectral e combate de forma eficaz o desvanecimento através da combinação dos sinais independentes, provenientes das múltiplas antenas. Além disso, esta combinação consegue proporcionar um ganho de multiplexagem que melhora a performance da rede.

Esta dissertação foca-se na implementação e avaliação da modulação GFDM, para os diferentes tipos de estruturas de antenas SISO, SIMO e MIMO. Em primeiro lugar, implementou-se o sistema SISO-GFDM, conside-rando a adição de ruido branco Gaussiano e desvanecimento de Rayleigh do canal. Vários equalizadores no domínio da frequência foram implemen-tados para mitigar o desvanecimento e remover a ICI (interferência entre portadoras) residual, tais como os equalizadores MF e ZF. Posteriormente, o sistema SISO para um único utilizador for estendido para um sistema SIMO e MIMO multiutilizador, onde um conjunto de utilizadores equipados com apenas uma antena transmitem, usando os mesmos recursos rádio, para uma estação base equipada com múltiplas antenas. Estes sistemas enfrentam interferências entre portadores e entre utilizadores que têm que ser mitigadas. Assim, foram projetados e implementados dois equalizadores sub ótimos, ZF e MMSE, para remover essas interferências. O sistema implementado GFDM é comparado como o OFDM em termos de taxa de erro (BER) e da densidade espectral de potência. Os resultados mostram que

(12)

(13)

Keywords 5G, Beyond 5G, Modulation schemes, GFDM, MIMO, Interference Cancella-tion techniques.

Abstract The Orthogonal Frequency Division Multiplexing (OFDM) technology has been used in 4G and 5G mobile telecommunications systems. Despite its features and advanced results, it has some challenges to enhance spectral efficiency. Generalized Frequency Division Multiplexing (GFDM) is a new dig-ital non-orthogonal multicarrier modulation concept. It aims to achieve higher spectral efficiency, better control of Out-Of-Band (OOB) emissions due to its flexibility to choose the pulse shaping filter, and obtain a reduction in Peak to Average Power Ratio (PAPR) compared to the OFDM. MIMO can further improve the spectral efficiency of the wireless network and has adopted in several standards. Therefore, the combination of MIMO transmission with GFDM technique is almost able to present optimum results due to its ability to have diversity gain by combining independent signals from multiple antennas in order to mitigate the fading phenomenon. Besides, it can also achieve multiplexing gain that improves the throughput of the networks.

This study addresses the implementation and evaluation of a GFDM system for different antenna structures such as SISO, SIMO, and MIMO. First, SISO-GFDM system is implemented, considering Additive White Gaussian Noise (AWGN) channel and Rayleigh fading channel. Several frequency domain equalizers are used to mitigate the fading and remove the residual Inter-Carrier Interference (ICI) such as Matched Filter (MF) and Zero Forcing (ZF) equalizers. Then, the system was extended to SIMO and Multi-User MIMO (MU-MIMO), where a set of single-antenna users transmit to the base station, equipped with a multi-antenna array, using the same radio resources. In MU-MIMO system besides the ICI, it also suffers from multi-user interference. Therefore, in this case, two sub-optimal receiver equalizers have been implemented to deal with both ICI and multi-user interferences such as (ZF and MMSE equalizer). The GFDM system is compared with the OFDM in terms of bit error rate (BER) and power spectral density. The results show that the Interference Cancellation (IC) techniques (Serial Interference Cancellation (SIC) and Double Sided Serial Interference Cancellation (DSSIC)) are quite

(14)

(15)

Acronyms

0G Generation 0

16-QAM 16 Quadrature Amplitude Modulation 1G First Generation

2G Second Generation

3G Third Generation

3GPP Third Generation Partnership Project 3GPP2 Third Generation Partnership Project 2

4G Fourth Generation

5G Fifth Generation

6G Sixth Generation

AMPS Analog Mobile Phone System AWGN Additive White Gaussian Noise

BER Bit Error Rate

CDMA Code Division Multiple Access CDMA EV-DO CDMA EVolution-Data Only

CP Cyclic Prefix

CSI Channel Sate Information D2D Device-to-Device

DAS Distributed Antenna System

dB Decibels

D-BLAST Diagonal Bell Labs Space-Time Architecture DFDMA Distributed Frequency Division Multiple Access DFE Decision-Feedback Equalization

DFT Discrete Fourier Transform DoF Degrees-of-Freedom

DSSIC Double Sided Serial Interference Cancellation DTV Digital Television

EDGE Enhanced Data GSM Evolution EGC Equal Gain Combining

FBMC Filter Bank Multi Carrier FDD Frequency Division Duplex

FDMA Frequency Division Multiple Access FFT Fast Fourier Transform

GFDM Generalized Frequency Division Multiplexing GPRS General Packet Radio Services

(16)

GSM Global System for Mobile communication

HD High Definition

HSPA High Speed Packet Access

HSDPA High Speed Downlink Packet Access HSUPA High Speed Uplink Packet Access IC Interference Cancellation

ICI Inter Carrier Interference

IDFT Inverse Discrete Fourier Transform

IEEE Institute of Electrical and Electronics Engineers IFFT Inverse Fast Fourier Transform

IMT International Mobile Telecommunications IMTS Improved Mobile Telephone System IoT Internet of Things

IP Internet Protocol ISI Inter Symbol Interference

ITU International Telecommunication Union LAN Local Area Network

LFDMA Localized Frequency Division Multiple Access LOS Line-of-Sight

LSTC Layered Space-Time Code LTE Long Term Evolution M2M Machine-to-Machine

MF Matched Filter

MIMO Multiple Input Multiple Output MISO Multiple Input Single Output

mMIMO Massive Multiple Input Multiple Output MMS Multimedia Message Service

MMSE Minimum Mean Square Error mmW millimeter Wave

MRC Maximal Ratio Combining MTS Mobile Telephone System

MU-MIMO Multiple-User MIMO

NFV Network Function Virtualization NLOS Non Line-of-Sight

OFDM Orthogonal Frequency Division Multiplexing OFDMA Orthogonal Frequency Division Multiple Access

OOB Out-Of-Band

OQAM Offset Quadrature Amplitude Modulation PAPR Peak to Average Power Ratio

PDF Probability Density Function PDP Power Delay Profile

PL Path Loss

PSD Power Spectral Density

PSTN Public Switched Telephone Network

PTT Push To Talk

QoS Quality of Service

(17)

QPSK Quadrature Phase Shift Keying RAT Radio Access Technology

RF Radio Frequency

RRC Root Raised Cosine SC Selection Combining

SC-FDMA Single Carrier FDMA

SDN Software Defined Networks SIC Serial Interference Cancellation SIMO Single Input Multiple Output SISO Single Input Single Output SMS Short Message Services SNR Signal-to-Noise power Ratio

STBC or SFBC Space-Time/Frequency Block Coding STTC Space-Time Trellis Code

SU-MIMO Single-User MIMO

SVD Singular Value Decomposition TDD Time Division Duplex

TDMA Time Division Multiple Access UFMC Universal Filtered Multi Carrier

UMTS Universal Mobile Telecommunication System V-BLAST Vertical Bell Labs Space-Time Architecture WAN Wide Area Network

WAP Wireless Application Protocol

WCDMA Wide band Code Division Multiple Access WiMAX Worldwide Interoperability for Microwave Access WLAN Wireless Local Area Network

WRAN Wireless Regional Area Networks

WWW World Wide Web

(18)

(19)

List of Figures

1.1 Cellular mobile communications evolution [5] . . . 2

1.2 GSM network architecture [10] . . . 3

1.3 Comparison between 1G, 2G, and 3G [12] . . . 4

1.4 Comparison between the principle of OFDMA and CDMA [15] . . . 6

1.5 Comparison between 4G and 5G mobile telecommunications networks [16] . . . 7

1.6 5G use cases [19] . . . 8

2.1 Radio wave propagation mechanisms . . . 13

2.2 Components of channel response . . . 14

2.3 Channel modeling [26] . . . 14

2.4 Fast Fading and Slow Fading [33] . . . 16

2.5 Rayleigh distribution PDF [35] . . . 18

2.6 Rician distribution PDF [36] . . . 19

2.7 The orthogonality concept in OFDM Signal [40] . . . 20

2.8 Block diagram of an OFDM system [41] . . . 21

2.9 The duration of OFDM [41] . . . 22

2.10 The duration of OFDM after inserting the Cyclic Prefix [41] . . . 23

2.11 The difference between OFDM and OFDMA [43] . . . 24

2.12 Block diagram of an SC-FDMA system [41] . . . 25

2.13 Subcarrier mapping methods for multiple users [41] . . . 26

2.14 Block diagram of an FBMC system [20] . . . 27

2.15 Block diagram of an UFMC system [20] . . . 28

2.16 GFDM Transmitter System Model [48] . . . 29

2.17 GFDM Receiver System Model [48] . . . 30

2.18 The self-interference in the k-th subcarrier from adjacent subcarriers [48] . . . . 30

3.1 Single and Multiple antennas configurations [50] . . . 32

3.2 Time diversity illustration [53] . . . 34

3.3 Performance of repetition coding [53] . . . 34

3.4 Space antennas diversity [53] . . . 35

3.5 Receive diversity scheme [53] . . . 36

3.6 MIMO System [53] . . . 40

3.7 Schematic of linear receiver architectures [53] . . . 41

(22)

4.2 Low complexity SISO-GFDM receiver system model [56] . . . 47 4.3 Block diagram of a SISO-GFDM receiver with the equalization process . . . 49 4.4 SISO-GFDM receiver with Interference Cancellation block [48] . . . 49 4.5 Interference Cancellation Unit [48] . . . 50 4.6 Basic SIC flowchart [48] . . . 51 4.7 Double Sided SIC flowchart [48] . . . 52 4.8 SISO-GFDM BER performance for QPSK modulation with different roll-off-factor and

AWGN channel used . . . 53 4.9 SISO-GFDM BER performance for QPSK modulation with different roll-off-factor and

multipath channel used . . . 54 4.10 SISO OFDM and GFDM Basic SIC and DSSIC BER performance for QPSK modulation

with α = 0.5 and AWGN channel used . . . 55 4.11 SISO OFDM and GFDM Basic SIC and DSSIC BER performance for QPSK modulation

with α = 0.5 and multipath channel used . . . . 56 4.12 Low complexity SIMO-GFDM receiver system model for 2Rx antennas . . . 57 4.13 SIMO OFDM and GFDM BER performance for QPSK modulation and 2Rx antennas with

different roll-off-factor and multipath channel used . . . 58 4.14 SIMO OFDM and GFDM BER performance for QPSK modulation and 2Rx antennas with

α = 0.5 and multipath channel used . . . . 59

4.15 SIMO OFDM and GFDM BER performance for QPSK modulation and 4Rx antennas with different roll-off-factor and multipath channel used . . . 59 4.16 SIMO OFDM and GFDM BER performance for QPSK modulation and 4Rx antennas with

α = 0.5 and multipath channel used . . . . 60

4.17 Low complexity 2_{× 2MIMO-GFDM transmitter system model . . . .} 61 4.18 2_{× 2MIMO channels . . . .} 61 4.19 Low complexity 2_{× 2MIMO-GFDM receiver system model . . . .} 62 4.20 2_{× 2MIMO OFDM and GFDM BER performance by using ZF equalizer for QPSK}

modulation with α = 0.5 and multipath channel used . . . . 63 4.21 2_{× 2MIMO OFDM and GFDM BER performance by using MMSE equalizer for QPSK}

modulation with α = 0.5 and multipath channel used . . . . 64 4.22 4× 4MIMO OFDM and GFDM BER performance by using ZF equalizer for QPSK

modulation with α = 0.5 and multipath channel used . . . . 64 4.23 4× 4MIMO OFDM and GFDM BER performance by using MMSE equalizer for QPSK

modulation with α = 0.5 and multipath channel used . . . . 65 4.24 2x4MIMO OFDM and GFDM BER performance by using MMSE equalizer for QPSK

modulation with α = 0.5 and multipath channel used . . . . 65 4.25 PSD comparison between OFDM and GFDM with α = 0.5 of RRC pulse shaping filter . 66

(23)

List of Tables

2.1 Parameters of a well designed OFDM System [41] . . . 23

4.1 OFDM and GFDM Simulation Parameters . . . 52 4.2 Power Delay Profile used in simulation [25] . . . 54

(24)

(25)

CHAPTER

1

Introduction

The overview of history and birth of radio communications generations is the main topic, before explaining the motivations and objectives of this dissertation, in terms of the features of every generation, started with First Generation (1G) to end with Fifth Generation (5G) of the wireless system. Then, it is presented the structure of this document.

1.1 History and evolution of mobile telecommunications

The birth of radio communication was between the 19th and 20th centuries. Many experiments and theories were studied and proven before talking about radio communication, starting with Faraday that predicted the existence of electromagnetic fields to James Clerk Maxwell in 1864, who was focused on his theoretical and mathematical researches to clarify that the electromagnetic waves could be propagated through free space [1]. Besides many scientists worked on this subject by testing a series of experiments to prove Maxwell’s theory. In 1886–88, Heinrich Rudolf Hertz confirmed the existence of Maxwell’s electromagnetic waves by using the frequency in the radio spectrum [1].

There are many interested people who are wondering about the first radio communication and the first mobile phone in the history of science. The Italian inventor Guglielmo Marconi in 1895 was the first scientist in using the radio waves for successfully transmitting and receiving radio signals. Therefore, transmitting weather information was the first voice transmissions over a distance of about one mile in 1900, and in 1901 he achieved transmitting the first voice communication crossed the Atlantic. Then, many scientists and engineers started working to develop and improve the ways of communications by using Radio Frequency (RF) waves [1] [2]. While in the 1970s at Motorola, the engineer Martin Cooper was worked to invent the first mobile phone that was considered the first generation of mobile communi-cation, where it was a handheld device, was able to make of two-way connection wirelessly. This led to an evolution of many technologies and standards in wireless systems in the future [2].

(26)

The development of cellular wireless communications systems was not limited to a specific stage, it had gone through several evolution stages from simple technologies to more developed ones that are using in our life and nowadays has experienced a remarkable change. This returns to the huge demand for more advanced connections to serve more users at the same time [3]. In the last few decades, it can be noted the advancement of mobile wireless communication through the Generations (G) that refers to a change in the nature of the system and each one has some standards in terms of the technology used, data rates, frequency, speed and so on. It was started with the First Generation 1G, Second Generation (2G), ..., ending with an upcoming generation 5G and the innovation of generations is still going on [4]. The evolution of mobile generations will be described to identify the advanced wireless technologies that were used and explaining how improvements have been made from the 1G to the next ones as shown in figure 1.1.

Figure 1.1: Cellular mobile communications evolution [5]

Wireless system is began with pre-cellular mobile telephony technology that indicated to Generation 0 (0G) [6]. It is used by public services such as police radiotelephones. 0G involves different technologies as Push To Talk (PTT), Mobile Telephone System (MTS), and Improved Mobile Telephone System (IMTS) [6]. Pre-cell phone mobile technology was developed in the 1970s to arrive the first generation of mobile network [7].

1G

The first generation of mobile network started deploying in Japan in 1979 to arrive US, Finland, UK and Europe in the beginning of 1980s, where the first mobile phones were introduced in 1982 and continued until the early of 1990. It was based on Analog Mobile Phone System (AMPS) technique that depends on analog radio signals only for voice services. The voice call can be modulated by Frequency Division Multiple Access (FDMA) with bandwidth of 10 MHz, channel capacity of 30 KHz and frequency band of 800 and 900 MHz with velocities up to 2.4kbps [4]. Due to the technology limitations, this system has many disadvantages. It has low and limited capacity, poor voice quality, unreliable handoff, poor battery life, large phone size, less security, limited number of users, very low level of spectrum efficiency, and there is no possibility for roaming between similar systems [4] [6] [8].

(27)

2G

The 1G is analog telecommunication standard uses circuit switching, continued until has been replaced by 2G in late 1980s and finished in late 1990s that uses circuit switching as well as packet switching and based on digital signals for voice transmission besides the Short Message Services (SMS), and Multimedia Message Service (MMS) at low speed from 14.4 to 64kbps data rate [9] with bandwidth of 20-200KHz [8]. Unlike the 1G systems, 2G systems provide the Internet service and thus the core network used is Public Switched Telephone Network (PSTN) [3]. 2G phones used a new digital technology for wireless transmission known as Global System for Mobile communication (GSM) technology as shown in figure 1.2, it uses digital modulation to improve the voice quality that based on Time Division Multiple Access (TDMA) and Code Division Multiple Access (CDMA) standards, in addition to use the CODEC for compressing and multiplexing digital voice data [8]. 2G systems used combination of TDMA and FDMA which means each frequency slot is divided into time slots, i.e., multiple users are able to connect the network with a specific frequency slot [3] [10]. This led to better quality and capacity, enhance the spectral effieciency, security, and the number of users. Besides the roaming, encrypted voice transmission and SMS services [4] [9].

Figure 1.2: GSM network architecture [10]

Although the lower data rate of 2G systems and the limited number of users and hard-ware capability, the demand of using its services experienced exponential growth in mobile telecommunication systems and this led to develop the cellular wireless technology to 2.5G system for acheiving higher data rate between 64-115kbps [8] and based on General Packet Radio Services (GPRS) that was introduced and successfully deployed. Beside Enhanced Data GSM Evolution (EDGE) that is considered 2.75G and an extended version of GSM, is able to support up to 473.6kbps [11]. 2.5G and 2.75G networks support services like Wireless Application Protocol (WAP), mobile games and Internet communication services such as send/receive emails, web browsing, camera phones [8] [10].

(28)

3G

From 2G to Third Generation (3G) technology, which means increasing the data rate trans-mission to reach 2Mbps [3] [12]. This technology was launched in the year 2000, supported for multimedia cell phone (smartphone) [8]. 3G is based on International Telecommunication Union (ITU) standards under the International Mobile Telecommunications (IMT) program (IMT-2000) [6] [12]. In 2G systems, to download a 3 minutes MP3 song, this will take time about 6-9 minutes [4], while in 3G system it needs just around 11 seconds for downloading [8]. This led to increasing the bandwidth and transfer rate for accommodating the applications that depend on web and audio and video files. Besides offer users with a wider range of advanced services and this requires improving the spectral efficiency and achieving a greater network capacity [6] [12]. Figure 1.3 shows the comparison between the previous generations with 3G.

Figure 1.3: Comparison between 1G, 2G, and 3G [12]

Herein, the core network used is a combination of Circuit switching and Packet switching where several access technologies had an important role in this wireless generation such as CDMA and Wide band Code Division Multiple Access (WCDMA). In CDMA, for each user, there is a unique code for using the channel at the same time, which means each user is able to use completely the available bandwidth and thus a large number of users have the ability to use the channel simultaneously [3]. It provides a 1.25MHz channel width with a data rate up to 144kbps [8]. In WCDMA or Universal Mobile Telecommunication System (UMTS), more amount of users can use the channel in comparison with CDMA, it has 5MHz channel width with data rate up to 2Mbps [8]. Therefore, the main features of 3G are: achieving higher data rate and higher quality 3D games, provides faster communication and mobile applications, enhanced security, supporting location tracking, maps and TV streaming, and enhanced audio and video streaming. But all of these require higher bandwidth and large and expensive 3G cell phones [4] [6] [11].

For standarization of 3G technologies, Third Generation Partnership Project (3GPP) and Third Generation Partnership Project 2 (3GPP2) were created to work for that purpose and both of them are based on CDMA although the carrier bandwidth and data rates were different. Besides defining technologies for achieving higher data rates above 1Mbps [13] by using the time division among the data flows on the downlink within the cell. 3GPP system is

(29)

also called High Speed Packet Access (HSPA) while 3GPP2 ia called CDMA EVolution-Data Only (CDMA EV-DO).

Enhancing the data rate is always required and thus was existing in 3G systems by applying two improvement technologies which are: High Speed Downlink Packet Access (HSDPA) and High Speed Uplink Packet Access (HSUPA). HSDPA is considered 3.5G, based on WCDMA with data transmission speed up to 8-10Mbps with a bandwidth of 5MHz [6] [12]. While HSUPA refers to 3.75G, it has higher data rate, is an improving uplink speed of UMTS / WCDMA system to be initially up to 1.4Mbps and then it reached to 5.8Mbps in the later releases [6] [12]. These two mobile telecommunications technologies are related and complimentary to each other and allow the possibility to the concept of Multiple Input Multiple Output (MIMO) system to be introduced and thus the data rate can reach to more than 42Mbps [3].

4G

Moving to the Fourth Generation (4G) systems means achieving higher data rate speed of 100Mbps for mobile user [8] [6] and up to 1Gbps for fixed stations [6] and thus higher quality audio/video streaming. To make this system efficient, it is necessary to design of new terminals. 4G is considered as a successor to 2G and 3G standards and the extension of 3G technology with more advanced multimedia services offers and more bandwidth. Noting that the core network used is based on Internet Protocol (IP) and the frequency band is between 2000 to 8000MHz with frequency spectrum used between 5-20MHz [3].

In this generation of cellular telecommunication systems, Long Term Evolution (LTE) is considered a 4G standard, it is designed by the ITU in the late 1990s [14] and based on GSM / EDGE and UMTS / HSPA technologies [3]. It is able to achieve around 100Mbps for downlink speed and 50Mbps for uplink speed [3]. 3G technologies are developed by ITU to IMT-2000 which was focused on publishing a set of requirements for 3G cellular communication systems and this led to launch another process which is IMT-Advanced by publishing a set of requirements for a 4G mobile communication system in 2008 [14]. The requirement of ITU for the second process IMT-Advanced exceeded the capabilities of LTE because it needed at least 600Mbps for downlink and 270Mbps for uplink with a bandwidth 40MHz [14]. Therefore, 3GPP was found that LTE-Advanced is able to improve and enhance the capabilities of LTE by achieving a maximum data rate of 1000Mbps for the downlink and 500Mbps for the uplink and according to this standards, LTE-Advanced was designed to be compatible with LTE [14].

In the other hand, the multiple access techniques are able to allow the base station to communicate with different mobiles simultinuously and thus 4G systems use multi carrier schemes such as Orthogonal Frequency Division Multiple Access (OFDMA) technique due to the data traffic is different from voice and it needs high peak rates just for short durations

(30)

[13]. Besides, in case of using multiple antennas, Orthogonal Frequency Division Multiplexing (OFDM) as shown in figure 1.4 is better than CDMA due to the orthogonality where the high data rate modulated stream is placed into many modulated narrowband closed-spaced subcarriers and thus improving the throughput by using a new dimension of spatial diversity [3] [15]. OFDMA technique is used as a downlink multiple access technique while Single Carrier FDMA (SC-FDMA) is used as an uplink multiple access technique (more details about OFDM and SC-FDMA are described in chapter 2).

Figure 1.4: Comparison between the principle of OFDMA and CDMA [15]

Therefore, 4G has many features complementary to 3G such as achieving higher data rate up to 1Gbps and higher quality video streaming, high security and mobility, expanded multimedia services to include digital television in High Definition (HD) technique and reduced latency for mission critical applications. However, 4G requires complicated expensive hardware and infrastructure because it needs high end mobile devices compatible with 4G technology and also uses more battery [4] [7].

5G

As highlighted before, it can be noted that 4G is one of the most used and dominant cellular communications technologies in the world by delivering the required speeds. Although all features of previous generations, there are still some challenges such as high energy consumption and the spectrum efficiency that can not be accommodated by 4G mobile telecommunication systems. Therefore, 5G in the near future is considered the next wireless system that will be deployed in 2020 [9]. The comparison between 4G and 5G is depicted in figure 1.5, where with 5G technology, it can be possible to handle best and advanced technologies [9] with much reliability, ultra-fast Internet and multimedia services, better levels of connectivity and coverage, and without the limitations and obstacles of the previous generations [6].

(31)

Figure 1.5: Comparison between 4G and 5G mobile telecommunications networks [16] 5G seeks to extend the frequency bands used for mobile telecommunications systems, besides using advanced modulation techniques to be able to achieve its features by applying small cell deployment, and utilizing wider frequency spectrum. This requires frequency bandwidth for cellular phones ranging between several hundred MHz to several GHz [7], to achieve data rate speed up to 10Gbps [17]. Therefore, 5G networks will be operated in the millimeter waves (fall between 30 and 300GHz band of the spectrum) which means a high spectrum frequency band between 28GHz and 60GHz [5].

Furthermore, designing the 5G cellular architecture has the main role in this kind of mobile generation. It is worked for separating the outdoor and indoor scenarios to avoid the obstacles and penetrations through buildings walls. Distributed Antenna System (DAS) and massive MIMO technology are working to achieve that [7]. This will lead to use smart beam antenna systems. In addition, 5G technology will be a single unified IP standard of different wireless networks and a combination of wireless technologies broadband such as Local Area Network (LAN), Wide Area Network (WAN), Institute of Electrical and Electronics Engineers (IEEE)802.11, and highly supportable to wireless World Wide Web (WWW) technology [4]. It also uses beamforming technology to improve the spectrum efficiency by applying massive element antenna technologies [18].

Figure 1.6 summarizes the use cases of 5G and it can summarize its features as: it has higher security and reliability with low latency in milliseconds [19], i.e. low latency with a round-trip delay of 1ms [20] (this is because of the new distributed network of base station) [17], achieving ultra-fast mobile Internet (up to 10Gbps in indoor and outdoor environments and 100Mbps in urban and suburban environments) [17], providing high speed and capacity [19] (up to 25 Mbps connectivity speed [4]), low power consumption, clarity in audio/video by HD Clarity technique, high resolution for cell phone user besides achieving a high broadcasting data (in Gbps) in terms of supporting almost 65000 connections [4]. In addition, 5G will be used by smart appliances remotely besides the closed-circuit cameras that provide security and high quality. 5G is not limited in a specific stage, but it can reach to so-called Internet of Things (IoT) which means connecting the applications, appliances, sensors, objects, and

(32)

devices with the Internet and this requires transmitting, collecting, analyzing and processing data in an efficient network [5]. Moreover, health care can be included in the features of 5G in terms of the smart medical devices that have the ability to make remote surgery [5].

Figure 1.6: 5G use cases [19]

Last but not least, the capabilities of 5G wireless technology are still introducing more features and seek to achieve higher data rates, low latency, ultra-high reliability, higher capacity, and massive device connectivity. Therefore, it is necessary to work with combination of many advanced technologies such as Software Defined Networks (SDN), Network Function Virtualization (NFV), Interference Cancellation (IC), Device-to-Device (D2D), Machine-to-Machine (M2M), multiple Radio Access Technology (RAT), besides advanced multiple antenna techniques MIMO and massive MIMO [17].

Currently, the researchers are still working towards the next generations of wireless com-munications beyond 5G or Sixth Generation (6G), which means using higher frequencies than the ones used in 5G to achieve more data rates speed [21]. Therefore, these new generations should be able to solve the problems that were faced the previous generations especially in the areas that 5G is not able to achieve high enough data throughput or low enough latency [21].

1.2 Motivation and Objectives

The specifications of the future wireless networks 5G for 2020 were almost defined, where OFDM was already adopted. However, because it has some drawbacks such as high Peak to Average Power Ratio (PAPR) and high Out-Of-Band (OOB) emissions, it is of paramount importance to propose and evaluate new different modulation schemes for future systems (beyond 5G or 6G). In recent years, some different schemes such as Filter

(33)

Bank Multi Carrier (FBMC), Universal Filtered Multi Carrier (UFMC), and Generalized Frequency Division Multiplexing (GFDM) have been proposed. Herein, GFDM modulation technique is considered the generalization of OFDM and the most flexible nonorthogonal multicarrier transmission scheme in comparison with the other multicarrier modulations techniques. The main purpose of GFDM is dividing the available spectrum into multiple spectral segments for each user and thus each segment has a different bandwidth [22]. It can be considered that GFDM is able to combine the flexibility and simplicity of OFDM with advanced mechanisms to avoid interference [23]. In addition to this, MIMO technology also has the main role in 5G wireless network due to its ability to achieve a higher data rate, better spectral efficiency, diversity, and multiplexing gain. Therefore, the combination of GFDM technique with MIMO can be considered as near-optimum detection schemes [24]. Moreover, GFDM uses one Cyclic Prefix (CP) between GFDM frames unlike OFDM that requires a CP between two time slots. Noting that both schemes employ the CP to avoid the Inter Symbol Interference (ISI), but in GFDM the interference between time slots can be avoided by choosing an appropriate pulse shaping filter [25] and this leads to better spectral efficiency [23].

GFDM reduces PAPR and has low OOB radiation in comparison with OFDM (that has this problem because of the rectangular pulse shaping filter used in the transmitter [24]) and this gives GFDM more capability for spectrum fragmentation [22] [23] [25]. On the other hand, the main drawback of GFDM is the Inter Carrier Interference (ICI) since one band suffers interference from the two adjacent bands and thus more complex receivers should be employed as compared with OFDM. The receiver design should deal with both ICI and the channel fading [25].

The objectives and contributions of this work include,

1. Implementation and evaluation of a single-user SISO-GFDM system, recently proposed in the literature.

2. Extension of this system to Single Input Multiple Output (SIMO) system, then to multi-user scenarios and terminals equipped with multiple antennas, i.e., a Multi-User MIMO-GFDM system. Most of the works in the literature only consider simple single-user Single Input Single Output (SISO) scenarios and therefore is quite important to access GFDM systems in more realistic multi-user MIMO scenarios.

3. For both systems, two different receivers are used: Matched Filter (MF) and Zero Forcing (ZF) receivers. Besides applying the IC techniques that are playing an important role in improving the performance of GFDM system. These techniques: Serial Interference Cancellation (SIC) and Double Sided Serial Interference Cancellation (DSSIC) were applied to GFDM-MF receiver.

4. In addition, since GFDM suffers from ICI, it is needed to employ different linear equalization techniques for each scenario such as ZF and Minimum Mean Square Error (MMSE).

(34)

The implemented GFDM systems are evaluated under realistic multipath Raleigh fading channels. Where the performance is compared with the conventional OFDM systems and presented in terms of Bit Error Rate (BER). Furthermore, one of the most important advantages of the GFDM is the reduction of the OOB radiation and thus the Power Spectral Density (PSD) of the GFDM is computed and also compared with the one obtained with the OFDM system.

1.3 Structure of the dissertation

This document is divided into more four chapters are organized as follows:

Chapter 2 presents an overview of the radio communications’ basic concepts in terms of radio propagation mechanisms and channel characterization. It also presents the OFDM modulation adopted by LTE and also by 5G systems. Then, it is presented the most relevant modulation schemes that can be used in the future systems.

Chapter 3 introduces the multiple antennas technologies, starting with an introduction to MIMO systems, highlighting the diversity and its types. Then, it presents the concept of multiplexing and finally the linear receiver architectures that used in MIMO systems.

Chapter 4 presents the implementation of GFDM system model in different cases: SISO, SIMO with 2 or 4 antennas, and MIMO system for 2 and 4 transmit-receive antennas. Then, comparing the BER performance of all systems with OFDM and also implementation the PSD of both schemes.

Chapter 5 presents the main conclusions and possible future work.

(35)

CHAPTER

2

Basic Concepts

Talking about the digital era means getting all the information we need by access the Internet. The sophisticated technologies have the main role in changing our daily life because it is working for many mind-blowing discoveries and better facilities in order to achieve easier electronic communication everywhere. For this reason, it must be necessary to keep going in achieving higher capacity, higher data rate, and better Quality of Service (QoS). Transferring the information between two or many points over the air requires appropriate signal formatting and terminals equipped with multiple antennas to efficiently deal with the adversity of the propagation channel. This chapter covers some of the most basic concepts related to the wireless system in terms of the wireless channel models and the modulation schemes that are necessary for future communication systems.

2.1 Wireless Channel Models

The channel in wireless communication has an essential role in exchanging information between communication devices, which is considered as a medium between the transmitter and the receiver to transfer an information signal. The transmitted signal must be modified to take into account the physical processes that occur in the channel. Transferring the signal from the transmit antenna to the receive antenna has an effect on the characteristics of that signal, which depends on several factors, such as the environment (in case of existing buildings or any other objects that cause reflection, refraction and diffraction of the signal), the shadowing, the path of the signal, and the noise. Modeling the real-world environment is almost impossible task. Therefore, there are many channel models that approximate the effetcs of specific real-world environments.

(36)

between the transmitter and the receiver is h(t) and the received signal is y(t) as

y(t) = x(t) ⊛ h(t) + n(t), (2.1)

the received signal consists of two parts, the first part is obtained by applying the convolution on the transmitted signal and the channel response, while the second one corresponds to the noise component n(t) [26]. In the frequency domain, the convolution is converted to multiplication operation as

Y (f ) = X(f )H(f ) + N (f ). (2.2)

There are two main parameters that are used to determine the performance of digital transmission: the transmission bit rate and the bit error rate [27]. Herein, it is very important to mention Shannon’s formula that determines the channel capacity C of a band-limited information transmission channel with Additive White Gaussian Noise (AWGN) measured by bits per second (bps) [27], as

C = W log₂ 1 + S N , (2.3)

this formula gives an expression to determine the maximum achievable bit rate that is possible to be transmitted without errors over an ideal channel of bandwidth W measured in Hz and of a given Signal-to-Noise power Ratio (SNR)_NS in a non-logarithmic scale by using channel coding, where S is the average signal power and N is the average noise power, both measured in Watt [27]. Noting that S = EbR and N = N0W where Eb, R, and N0 represent

the bit energy in Joules (J), bit rate in bps, and the noise power spectral density in Watts/Hz respectively. Thus, Shannon’s formula can be expressed [27] as

C = W log₂ 1 + S N = W log₂ 1 + _E b N0 _R W . (2.4)

If R < C, the bit error rate can be made negligible and the efficiency of the channel capacity

C may increase in case of increasing the ratio R_C [27].

The received SNR is the power ratio between the received signal power Pr and the noise power Pn, and can be mathematically expressed as

SNR = Pr

N0B

. (2.5)

Each of these powers can be determined by several factors, where the received power is determined by the transmitted power, Path Loss (PL), shadowing and multipath fading while the noise power is determined by the bandwidth of the transmitted signal and the spectral properties [28]. In addition, the received SNR can be given in terms of the signal energy per bit Eb or per symbol Es as

SNR = Pr N0B = Es N0BTs = Eb N0BTb , (2.6)

where Tsis the symbol time and Tbis the bit time. Noting that for binary signaling SNR = _NEb₀

and for multilevel signaling SNR = Es N0 [28].

(37)

2.1.1 Radio-Propagation Mechanisms

The propagation of the signal from the transmitter to the receiver has many paths as illustrated in figure 2.1, if the signal reaches the destination through a single path without facing any kind of propagation mechanisms, this means that the signal is propagated in a Line-of-Sight (LOS) path. But, in case of propagating in one or more indirect paths, this called Non Line-of-Sight (NLOS) propagation [27].

Figure 2.1: Radio wave propagation mechanisms The main NLOS propagation mechanisms are [27] [29]:

• Absorption occurs when a radio wave passes through an object such as trees, where a part of the strength of this signal is absorbed as a heat. The resulting signal strength in the other side will be weak in this case.

• Reflection occurs when a radio wave hits an object has a wavelength much larger than the wavelength of the signal such as a wall. Thus, the signal will be reflected off the surface.

• Refraction occurs when a radio wave hits an object has a different density from the one which related to the signal such as a cloud. In this case the direction of the signal will be shifted from the original direction. Noting that the reflection is accompanied by the refraction, that means the strength of reflected or refracted waves depends on the type of object.

• Diffraction occurs when a radio wave impinges on a sharp surface such as mountains, irregular edges and tops of buildings. The signal will be diffracted (broken up) and bended around the sharp corners of the object to create few diffracted signals from the original one.

• Scattering occurs when a radio wave impinges on an object that has irregular dimensions smaller than the wavelength of the signal such as street signs and lamp posts. The signal will ricochet off the rough surface area of an object and create several signals from the original one. This leads to propagating the signal in a wide area and losing energy. In the end, the resulting signal will arrive at the receiver from almost the same location with slight differences in delay.

(38)

2.1.2 Propagation characteristics

In a realistic urban environment, the transmitted signal faces several obstacles because of the buildings, trees, and many other objects which affect the path of the signal that spread randomly as mentioned before in section 2.1.1. These phenomena originate three types of distinct variations on the received signal: Path Loss, Shadowing effect and multipath propagation as shown in 2.2.

Figure 2.2: Components of channel response

The left-hand side of figure 2.3 represents the logarithmic ratio of received-to-transmitted power in Decibels (dB) against the logarithmic distance [26], while the right-hand side of this figure shows the three components of the channel response: propagation PL, shadowing, and multipath fading.

Figure 2.3: Channel modeling [26]

The previous mechanisms lead to classify two main distinct scales of fading: Large Scale Fading and Small Scale Fading as,

(39)

Large-Scale Fading describes the average signal-power attenuation or Path Loss at the receiver after propagating over a large area and over a very long distance (hundreds of wavelengths). It also represents the fluctuations of the signal strength over distances from tens to hundreds of meters, where the power fluctuates around a mean value. The interference may cause a significant dropping (variation) in the strength of the signal caused by the obstacles during the paths. It could be estimated the path loss as a function of distance by two main factors: mean-path loss and log-normally distributed variation about the mean [26] [27] [30] [31].

If there is a strong attenuation, the signal will be blocked, and the received signal power variation due to shadowing can happen over distances (10-100 m in outdoor en-vironments and less in indoor enen-vironments) [28] that are proportional to the length of the obstructing objects. As a consequence of shadowing, the received signals which have the same distance from the transmitter, may have different received power and also a lognormal distribution. For that random attenuation, there is a need for a statistical model to characterize this attenuation, the most common one is log-normal shadowing model [28] [31].

Small-Scale Fading is also called multipath fading, it describes the very small changes of the amplitude and phase of the electromagnetic waves during propagating over a short distance (few of wavelength) and a short period of time (seconds) [27]. As mentioned, the signal is exposed to some obstacles during its path, which leads to several reflected signals, reaching the receiver at different time instants and with different intensities and phases. This phenomenon is usually called multipath propagation [26] [29]. Since each reflected signal has a different phase and amplitude, sometimes they are in phase and other times in an opposite phase, the overall received may have significant instantaneous power variations. So, the received signal power may be increased or decreased [26].

2.1.3 Channel characterization

The main parameters that characterize the multipath channel can be described as,

2.1.3.1 Doppler Spread and Coherence Time

According to [27], Doppler spread and coherence time are both parameters that describe the time-varying nature of channel causes frequency dispersion to determine if the channel is facing fast fading or slow fading in terms of the transmitted signal bandwidth Bs and

the symbol duration Ts. Noting that the Doppler spread Bd is inversely proportional to the

coherence time Tc.

Doppler Spread Bd is a range of frequencies that the received Doppler spectrum is nonzero

and is considered as a measure of spectral broadening caused by motion which means by the time rate of change of the mobile channel [27]. There are no effects of the Doppler spread and considered negligible at the receiver in case of the Doppler spread Bdis much lower than the

(40)

a low data rate such as a slow-fading channel.

Coherence Time Tc is a statistical measure of the time duration over which the channel

impulse response remains invariant. If the coherence time Tc of the transmitted signal is

much lower than the symbol period Ts, the channel will change during the transmissions of

the signal and this affects the signal and causes distortion [32]. Therefore, if there are two signals transmission with a symbol period greater than the coherence time, these two signals will be affected by the channel differently [27].

Small-scale fading based on Doppler spread causes the transmitted signal to go through fast fading in case of high Doppler spread or slow fading in case of low Doppler spread, as shown in figure 2.4.

Figure 2.4: Fast Fading and Slow Fading [33]

Fast Fading: it occurs when the symbol period of the transmitted signal Ts is greater than

the coherence time of the channel Tc [27] [31] as

Ts > Tc. (2.7)

This means that the impulse response of the channel changes rapidly during the symbol duration and this type of fading is expected to occur when the coherence time is about less than hundreds of symbol periods [27], noting that fast-fading phenomenon happens to a very low data rate [27] where the rate of change of the transmitted signal is smaller than the rate of change of the channel characteristics [32]. Therefore, the channel varies faster than transmitted base-band signal variations and it called a fast-fading channel.

Slow Fading: it occurs when the coherence time of the symbol period Ts is less than the

coherence time of the channel Tc [27] [31] as

Ts < Tc. (2.8)

This means that the impulse response of the channel changes at a rate much slower than the impulse response of the transmitted signal [32] and this type of fading is expected to

(41)

occur when the coherence time is almost in thousands of symbol periods [27]. Therefore, the channel variations slower than transmitted base-band signal variations and it called a slow-fading channel.

2.1.3.2 Delay Spread and Coherence Bandwidth

According to [27], Delay Spread and Coherence Bandwidth are both parameters that describe the time dispersion nature of the channel in a local area to determine if the channel is facing flat fading or frequency-selective fading in terms of the transmitted signal bandwidth

Bs and the symbol duration Ts. Noting that the coherence bandwidth Bc is inversely

proportional to the root-mean-square delay spread στ.

Delay Spread στ is the difference between the arrival time of the earliest component and

the arrival time of the latest component. Therefore, it is a random variable and also is considered in wireless communications as a measure of the multipath profile of the channel [27].

Coherence Bandwidth Bc is a statistical measure of the range of frequencies over which

the channel impulse response is considered flat, which means there is a possibility for all spectral components to pass through the channel with a linear phase and equal gain [27]. Therefore, if there are two signals transmission with a frequency separation greater than the coherence bandwidth, these two signals will be affected by the channel quite differently [32].

Small-scale Fading based on multipath time delay spread is divided into two types of fading. If there is a small delay spread, this will lead to Flat Fading, while if there is a large delay spread, this will lead to Frequency Selective Fading as,

Flat Fading: it occurs when all frequency components of the transmitted signal fall within the coherence bandwidth fade simultaneously [27] and the amplitude of the received signal changes with time [32]. Herein, the gain of the signal is constant and the phase is linear due to the coherent bandwidth Bc is greater than the bandwidth of the transmitted signal Bs [27]

[31] as

Bs< Bc. (2.9)

Frequency Selective Fading: it occurs when some frequency components in the transmitted signal fade, while other frequency components not fade [27]. Besides, the coherent bandwidth

Bc is smaller than the bandwidth of the transmitted signal Bs [27] [31] as

Bs> Bc. (2.10)

The channel is considered as a frequency-selective channel when there is a large spread in multipath delays and this causing ISI. Therefore, it is necessary to clarify two points [27]:

• If there is no mobility in a frequency-selective channel: the channel will be time-invariant and the Doppler shift is zero. Thus, there is a big need for the equalization process to minimize the effect of ISI.

(42)

• If there is mobility in a frequency-selective channel: the channel will be time-varying and the Doppler shift is nonzero.

While the channel is considered as a frequency-selective fading channel when the channels are dependent on frequency and also time-varying. As a result, these types of channels require a complex equalization because it is characterized by time-varying ISI [27] [32].

2.1.3.3 Fading distribution

In multipath propagation, there is a time-varying signal different from path to path where each path has diferent Doppler shift, time delay, and path attenuation [27]. Therefore, there are multipath propagation channels, each one has own characteristics. The best example for time-varying linear channel is called Rayleigh fading, which is used to simulate the small fluctuations when there is no direct ray component. If there are a large number of paths, the envelope of the received signal is statistically described in a case of NLOS component by a Rayleigh distribution and in case of LOS component is called Rician distribution [27] [34].

Rayleigh Distribution: it is considered as the worst fading type because all components of the received signal envelope distribution for channels are NLOS. As depicted in figure 2.5, when the component of the channel h(t) are independent, the Rayleigh Probability Density Function (PDF) of the amplitude r =_{|h| = α [34] is}

f (r) = r σ2e

−r2

2σ2, (2.11)

where E{r2_{} = 2σ}2 _{and r}_{≥ 0.}

Figure 2.5: Rayleigh distribution PDF [35]

Therefore, it is the most commonly used signal model in wireless communications where the power is exponentially distributed and the phase is independently distributed from the amplitude [34].

(43)

Rician Distribution: in this type of distribution, the components of the received signal envelope distribution for channels are LOS. This leads to a complex Gaussian channel with non-zero mean. The Ricean PDF of the amplitude r =_{|h| is depicted in figure 2.6, and can} be expressed mathematically [34] as f (r) = r σ2e −r2_2σ2+v2_I 0 _rv σ2 , (2.12)

where r≥ 0 and I0 is the modified Bessel function of order zero and 2σ2= E{α2}.

Figure 2.6: Rician distribution PDF [36]

Noting that h = αejφ_{+ ve}jθ _{where α follows the Rayleigh distribution (the amplitude)}

and v2 is the power of the LOS signal component where v > 0 is a constant value. The angle

θ and φ are assumed to be mutually independent and uniformly distributed on [_{−π, π] [34].}

The Rayleigh fading channel is equal to Rician fading channel if the Rice factor K→ ∞ where there is NLOS component and it can be expressed [34] as

K = v

2

2σ2, (2.13)

considering that it is a relation between the power of the LOS components (Rician component) and the power of the NLOS components (Rayleigh component).

The channel models are usually modeled by Power Delay Profile (PDP) and also called the multipath intensity profile, which is supplied as a table of values for different scenarios that can be used to simulate the channel. PDP represents the average power associated with a given multipath delay, where for each individual reflected path, there is a different time delay depending on the length of these signals [28].

(44)

2.2 Modulation Schemes suitable in 4G and 5G Technologies

The secured data communication and higher data rates transmission for the next-generations wireless communications are considered the main factors of increasing the demands on the QoS. The digital communications techniques become more developed and reliable, where it has the ability to operate at higher spectral efficiency. For this reason, the communi-cation systems are incorporating the multi-carrier transmission techniques to achieve their purpose of getting a higher data rate transmission. Therefore, Orthogonal Frequency Division Multiplexing (OFDM) was adopted in the 4G systems and will be also used in the 5G systems due to its ability to achieve high data rates. The main drawback of OFDM is the high PAPR and thus the Single-Carrier FDMA (SC-FDMA) is a modified form of Orthogonal Frequency Division Multiple Access (OFDMA), was developed for the LTE uplink. It has a similar throughput performance but with lower PAPR [37]. These techniques will be described in detail as follows:

2.2.1 Orthogonal Frequency Division Multiplexing (OFDM)

OFDM is a digital multi-carrier modulation technique that employs multiple carriers within the assigned bandwidth [38]. The basic principle of OFDM is to transmit, in parallel, a large number of a lower rate data stream over a number of different orthogonal subcarriers instead of transmitting high-rate data stream with a single subcarrier [39], which means splitting a big data stream into a high number of narrow band subcarriers. Noting that each one of these subcarriers is made orthogonal to one another [40], in order to be spaced very close together with no overhead as shown in figure 2.7. OFDM is able to be modulated with a specific type of digital modulation schemes such as Quadrature Phase Shift Keying (QPSK), 16 Quadrature Amplitude Modulation (16-QAM) and so on. In addition, the symbol duration is much larger than the source symbol duration on each subcarrier [27] and this reduces the impact of ISI. However, for eliminating the effect of ISI completely, the CP or guard interval was almost the solution to achieve that by introducing it between each OFDM symbol. Thus, the mechanism of this CP is summarized that the OFDM symbol will be extended cyclically to avoid the ICI between the adjacent subcarriers [39] [40].

Figure 2.7: The orthogonality concept in OFDM Signal [40] 20

(45)

The main goal of applying OFDM modulation is the orthogonality between the carriers because this helps in increasing the overall spectral efficiency of the system where there is no ICI between closely spaced carriers. First, it is necessary to choose the spectrum required that depends on the input bits data and the type of digital modulation where the data will be transmitted over independent carriers, each one has a required phase and amplitude. Thus, to ensure the orthogonality between the chosen carrier frequencies, the Inverse Fast Fourier Transform (IFFT) and Fast Fourier Transform (FFT) operations are considered the key to achieving that [27] [38] [41]. Herein, the basic model of OFDM transceiver is illustrated in figure 2.8.

Figure 2.8: Block diagram of an OFDM system [41]

At the transmitter, the input bits stream will be modulated first by using one of the digital modulation types and converted to parallel bits by serial-to-parallel conversion block. The parallel resulting flow was defined in the frequency domain, so IFFT is used to transform the data into the time domain. Then, to eliminate the ISI and ICI at the receiver caused by the multipath delay spread in the channel, it is necessary to add the CP to the beginning of the symbol which is a copy of the last part of the symbol [20]. The length of CP should be greater than the delay spread of the channel where in this case the length of symbols will be extended [42].

At the receiver, the same steps of the block diagram of the transmitter will be applied but in a reverse way. Starting to converting the analog signal to a digital one then removing the CP which was inserted between each of the symbols. The series of symbols will be divided into several symbols that should back to the frequency domain by FFT. In the end, the symbols will be converted to serial ones to be ready for the demodulation process for receiving the binary information sent by the transmitter [20] [42].

(46)

According to[41], considering that Nc is the number of subcarriers modulated with a

bandwidth B, the spacing between the subcarrier is given by ∆f = B

Nc

, (2.14)

while the symbol duration of OFDM signal for kth subcarrier where k = 0, ..., Nc− 1 is Tk =

1

∆f. (2.15)

Moving to the receiver before looking at the implementation of the transmitter, the received signal r(t) can be expressed as

r(t) = Re (_Nc−1 X k=0 dkrect(t/T )ej2πtfkej2πtfc ) , (2.16)

where dk is the complex data symbols for kth subcarrier, T is the duration of time slot, fk is

the symbol frequency of the kth subcarrier and fk is the carrier frequency refers to fk= _Tk.

Moreover, the received signal after removing the RF carrier which means after the baseband processing is given by s(t) = r(t)e−j2πfct = Nc−1 X k=0 dkej2πkt/T. (2.17)

In case of sampling the received signal at a rate of Nc

T , the set of Nc samples sn can be

expressed as sn= s(nT /Nc) = Nc−1 X k=0 dkej2πkn/Nc, (2.18)

where n = 0, 1, ..., Nc− 1, and this leads to expressing the relation between the sequance of

received signal sn at a rate of N_Tc and the sequance of complex data dk as

{sn} = IFFT{dk} ⇒ {dk} = FFT{sn}, (2.19)

this means that the implementation of the OFDM modulation can be carried out replacing the bank of modulators by an IFFT operation [41].

As mentioned before, the signal will be transmitted over a multipath channel, so it will not be confined to the duration of the OFDM time slot but will spread over TOF DM + τmax

where τmax is the maximum time delay, this leads to overlapping of OFDM symbols as shown

in figure 2.9.

Figure 2.9: The duration of OFDM [41] 22

(47)

Therefore, inserting of CP is really needed to a fully remove the ISI when the time of CP or guard interval is greater than the maximum time delay as TG> τmax and also causes a loss

in spectral efficiency because it reduces the transmission rate [41]. In the result, the duration of OFDM signal can be presented in figure 2.10 and written as

T_{OF DM}‘ = TOF DM+ TG. (2.20)

Figure 2.10: The duration of OFDM after inserting the Cyclic Prefix [41]

For designing a convenient OFDM system, there are few parameters as shown in table 2.1 that should be taken into consideration.

TCP > τmax ISI free

∆f >> 2fD,max ICI free

TOF DM << Tc Time invariance

Table 2.1: Parameters of a well designed OFDM System [41]

There are several advantages for OFDM modulation and it can be summarized as follows [20] [41] [42]:

• OFDM is highly reliable and more resistant because of dividing the subcarrier into several narrowband subcarriers.

• OFDM is more efficient to implement the modulation and demodulation processes by using IFFT and FFT operations.

• OFDM eliminates ISI and ICI by inserting of a CP which means increasing the symbol duration.

• OFDM shows that spectral efficiency increases as increasing the number of users. • OFDM has a very low symbol rate to make sure that all subcarriers are completely

orthogonal.

• OFDM has good performance in terms of flexibility and robustness in a frequency selective channel.

• OFDM requires a simple equalization technique in the frequency domain resulting from the low complexity of the base-band receiver, and in this case, the output signal has low distortion.

(48)

Eventhough these advantages, OFDM system has some drawbacks as [27] [42]:

• OFDM has more OOB emissions, this because of using the rectangular pulse shaping filter in the transmitter.

• OFDM has high PAPR, this because of the large peak signal that formed by the random sum of the phase subcarriers that occurs when the signals in the K sub-channels add constructively in phase. This means the amplifiers require a large power back-off. Therefore, to reduce this problem, it can be by phase adjustments or by peak clipping that may cause some distortion in the signal.

Moreover, OFDM modulation can be extended to OFDMA for the implementation of a multi-user communication system, where it allows to transmit low data rate from several users at the same time, i.e., OFDM system is allocating all of the available subcarriers while OFDMA is distributing just a subset or group of subcarriers to each user for being able to multiple transmission simultaneously, where each group is named a subchannel [41] [43], as shown in figure 2.11.

Figure 2.11: The difference between OFDM and OFDMA [43]

In addition, in OFDM technique, the issue of orthogonality of the subcarriers is considered almost easy, while in OFDMA, different users transmit at the same time, each one has own subcarrier frequencies, this causes a frequency offset that leads to creating a multiple access interference. OFDMA signals have also a high PAPR because in the time domain, the multicarrier signal consists of the sum of many narrowband signals, which can be added up constructively or destructively and this reduces the efficiency and increases the cost of the RF power amplifier to avoid the distortion [37] [44].

2.2.2 Single Carrier-Frequency Division Multiple Access (SC-FDMA)

SC-FDMA is a single carrier multiple access techniques, has similar performance and the same structure of OFDM. The main advantages of SC-FDMA over OFDMA is the lower PAPR of the transmitting signal. According to [41], SC-FDMA combines the low PAPR of single-carrier systems with robust resistance to multipath channels, lower complexity at the

Implementation and performance evaluation of MIMO GFDM systems

Joumana

Kassam

Implementação e avaliação do desempenho de

sistemas MIMO GFDM

Joumana

Kassam

Implementação e avaliação do desempenho de

sistemas MIMO GFDM

Implementation and performance evaluation of

MIMO GFDM systems

Joumana

Kassam

Implementação e avaliação do desempenho de

sistemas MIMO GFDM

Implementation and performance evaluation of

MIMO GFDM systems

Acronyms

Contents

List of Figures

List of Tables

CHAPTER

1

Introduction

CHAPTER

2

Basic Concepts