Hybrid precoding and equalizer techniques for mmWave and massive MIMO based wireless systems

(1)

Universidade de Aveiro 2020

Departamento de Eletrónica, Telecomunicações e Informática

Roberto Louro Magueta

Técnicas híbridas de pré-codificação e equalização

para sistemas sem fios baseados na banda das

ondas milimétricas e MIMO massivo

Hybrid precoding and equalizer techniques for

mmWave and massive MIMO based wireless

systems

(2)

(3)

Universidade de Aveiro 2020

Departamento de Eletrónica, Telecomunicações e Informática

Roberto Louro Magueta

Técnicas híbridas de pré-codificação e equalização

para sistemas sem fios baseados na banda das

ondas milimétricas e MIMO massivo

Hybrid precoding and equalizer techniques for

mmWave and massive MIMO based wireless

systems

Tese apresentada à Universidade de Aveiro para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Engenharia Eletrotécnica, realizada sob a orientação científica do Doutor Adão Paulo Soares da Silva, Professor Auxiliar do Departamento de Eletrónica, Telecomunicações e Informática da Universidade de Aveiro; do Doutor Rui Miguel Henriques Dias Morgado Dinis, Professor Associado com Agregação na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa; e do Doutor Daniel Filipe Marques Castanheira, Investigador do Instituto de Telecomunicações da Universidade de Aveiro.

Apoio financeiro da FCT e do FSE no âmbito do III Quadro Comunitário de Apoio – SFRH/BD/129395/2017

(4)

(5)

Dedico este trabalho aos meus pais pelo trabalho e a despesa que tiveram comigo ao longo destes anos, e à minha irmã que tantas vezes me fez o lanche depois de chegar a casa. Dedico ainda à Genabú Djassi, pois deu-me o propósito para tudo aquilo que fiz.

“Everyone is a genius. But if you judge a fish by its ability to climb a tree, it will live its whole life believing that it is stupid.”

(6)

(7)

O júri / The jury

presidente / presidente Doutor Vítor António Ferreira da Costa

Professor Catedrático da Universidade de Aveiro

vogais / examiners committee Doutor Marco Alexandre Cravo Gomes

Professor Auxiliar da Faculdade de Ciências e Tecnologia da Universidade de Coimbra

Doutor Fernando José da Silva Velez

Professor Auxiliar da Universidade da Beira Interior

Doutor Francisco António Bucho Cercas

Professor Catedrático do ISCTE-IUL - Instituto Universitário de Lisboa

Doutora Susana Isabel Barreto de Miranda Sargento

Professora Catedrática da Universidade de Aveiro

Doutor Adão Paulo Soares da Silva

(8)

(9)

Agradecimentos / Acknowledgements

Foremost, I would like to thank my supervisor, Professor Adão Silva, and my co-supervisors, Professors Daniel Castanheira and Rui Dinis, for supervising the process of my PhD thesis and guiding me through it. With them, I have learned and deepened my technical insight. The grant to be able to do the PhD, the papers I published, and the complex mathematical manipulations were achieved due to my supervisors.

I would also like to thank to Instituto de Telecomunicações, namely the secretary, who has handled the trips to conferences and was always diligent and agile solving all problems.

(10)

(11)

Palavras-chave 5G, terminais com número elevado de antenas, comunicações na banda das ondas milimétricas, arquiteturas híbridas analógico-digitais, sistemas OFDM com envolvente constante, bloco iterativo de equalização.

Resumo

As comunicações na banda das ondas milimétricas e a utilização de terminais equipados com um número elevado de antenas serão duas das tecnologias chave que possibilitarão os futuros sistemas de comunicação sem fios. A combinação destas tecnologias permitirá atingir os multi Gb/s necessários para atender aos requisitos de qualidade de serviço.

Uma vez que consideramos um número elevado de antenas, não podemos usar uma cadeia de radiofrequência por antena, devido ao consumo de potência e custos de hardware. A solução é o uso de arquiteturas híbridas, onde o número de cadeias de radiofrequência é menor que o número de antenas. Em tal arquitetura, o processamento é distribuído entre os domínios analógico e digital (contrariamente aos sistemas convencionais completamente digitais). Logo, as abordagens usadas nos sistemas convencionais completamente digitais não podem ser usadas nestas arquiteturas híbridas, onde um filtro analógico tem que ser calculado, para além de outras restrições de hardware adicionais. Portanto, este trabalho de investigação explora o projeto de técnicas de formação de feixe e equalização, assumindo terminais com um número elevado de antenas na banda das ondas milimétricas.

Uma das principais vantagens da exploração da banda das ondas milimétricas é permitir maiores larguras de banda, o que leva a um maior número de subportadoras para sistemas multiportadora. Portanto, a técnica orthogonal frequency division multiplexing (OFDM), que é bastante eficiente para mitigar os efeitos da interferência entre símbolos em canais seletivos na frequência, resulta num sinal com maiores flutuações em amplitude, tornando o elevado peak-to-average power ratio (PAPR) um problema que deve ser tido em conta para sistemas na banda das ondas milimétricas com um número elevado de antenas. O alto PAPR resulta em fortes distorções não lineares causadas pelos amplificadores de potência, degradando o desempenho do sistema. Para resolver o problema do PAPR, podem ser usadas modulações de envolvente contante que apresentam um PAPR igual a 0 dB, tal como a constant envelope OFDM (CE-OFDM). Portanto, este trabalho de investigação explora o projeto de uma técnica de equalização, especificamente para sistemas híbridos usando o CE-OFDM como técnica de modulação.

Adicionalmente, há um interesse significativo no projeto de equalizadores não lineares que têm sido considerados para eficientemente separar os dados de forma espacial, e mitigar o problema da interferência entre portadoras nos atuais sistemas multi-antenas, e que podem ser especialmente eficientes num cenário com um elevado número de antenas. O iterative block decision feedback equalization (IB-DFE) é um dos equalizadores não lineares mais promissores. Portanto, este trabalho explora os princípios do IB-DFE em sistemas híbridos. A primeira parte da tese foca no desenvolvimento de algoritmos eficientes para precodificação/formação de feixe e equalização, para um canal de banda estreita. Numa primeira fase são assumidos cenários de um utilizador, para separar os fluxos de dados espaciais, tendo sido depois esta solução estendida para cenários de múltiplos utilizadores, para reduzir a interferência entre estes. A segunda parte da tese foca no desenvolvimento de algoritmos para um canal de banda larga, que tem de ser diferente do caso de banda estreita, devido às especificidades das arquiteturas analógico-digitais. O CE-OFDM é também explorado como um meio para resolver o problema do PAPR. Estes algoritmos são acompanhados com resultados numéricos para avaliar os seus desempenhos.

Os resultados numéricos mostram que os algoritmos propostos para as arquiteturas analógico-digitais, baseados em processos iterativos, são bastante eficientes para remover a interferência entre utilizadores e entre símbolos. Os desempenhos obtidos com estes algoritmos quase alcançam o desempenho ótimo das arquiteturas convencionais completamente digitais, apenas com

(12)

(13)

Keywords 5G, massive MIMO, millimeter-wave communications, hybrid analog-digital architectures, constant envelope OFDM systems, iterative block equalization.

Abstract Millimeter wave communications (mmWave) and massive MIMO will be two of the keys enabling technologies for future wireless communication systems. The combination of these technologies will allow to achieve multi Gb/s needed to meet the quality of service requirements. In this research work we design solutions for mmWave massive MIMO systems, where a set of users equipped with a large number of antennas transmit data to a receiver also equipped with a massive number of antennas.

Since we consider a large number of antennas, we cannot use one dedicated RF chain per antenna, due to power consumption and hardware costs. The solution is the use of a hybrid architecture, where the number of RF chains is lower than the number of antennas. In such architecture the processing is distributed by the analog and digital domains (contrary to the conventional fully digital systems). Thus, the conventional fully digital approaches cannot be used in this hybrid architecture where an additional analog filter must be computed and we have additional hardware constraints. Therefore, this research work explores the design of beamforming and equalization techniques assuming massive antenna terminals for mmWave based systems, and to cope with the hardware limitations inherent to this type of systems, three hybrid analog-digital architectures are considered: the fully connected, and the subconnected with fixed or dynamic subarray antennas.

A major advantage of the exploration of mmWave bands is to allow larger bandwidths, which lead to larger number of subcarriers for multicarrier based systems. Therefore, the orthogonal frequency division multiplexing (OFDM) technique, which is very efficient to mitigate the effects of inter-symbol interference (ISI) in frequency selective channels, results in a signal with higher amplitude fluctuations, making the large peak-to-average power ratio (PAPR) a problem that should be taken into account for mmWave mMIMO systems. A high PAPR results in strong nonlinear distortions caused by the power amplifier, degrading system performance. To solve the PAPR problem, constant envelope modulations which present a PAPR equal to 0 dB, such as the constant envelope OFDM (CE-OFDM), can be used. Therefore, this research work explores the design of an equalization technique for hybrid analog-digital systems using the CE-OFDM as modulation technique.

Additionally, there is significant interest in the design of nonlinear equalizers, that have been considered to efficiently separate the spatial streams and mitigate the inter-carrier-interference (ICI) problem in the current MIMO systems, and that can be extremely efficient in a mMIMO scenario. Iterative block decision feedback equalization (IB-DFE) approach is one of the most promising nonlinear equalization schemes. Therefore, this work explores the IB-DFE principles for the hybrid analog-digital systems.

The first part of the thesis is focused on the development of efficient precoding/beamforming and equalization algorithms for a narrowband channel. In the first phase, a single-user scenario is assumed to separate the spatial streams and later the developed solution is extended for multiuser scenarios, to reduce the inter-user interference. The second part of the thesis is focused on the development of algorithms for a wideband channel, which have to be different from the narrowband case due to specificities of analog-digital architectures. The CE-OFDM is also exploited as a mean for solving the PAPR problem. These algorithms are accompanied with numerical results to evaluate their performance. The numerical results show that the proposed algorithms for analog-digital architectures, based on iterative procedures, are very efficient to remove the multi-user/inter-symbol interference. The performance obtained with these algorithms almost achieve the optimal performance of conventional fully digital architectures with a very few iterations. Therefore, they are interesting for practical mmWave massive MIMO based systems, since it ensures good performance at a low cost.

(14)

(15)

List of Figures

Fig. 1.1 - Keys and scenarios for 5G systems. ... 5

Fig. 2.1 - Allocation of data symbols for multi carrier transmission. ... 14

Fig. 2.2 - Allocation of data symbols for single carrier transmission. ... 14

Fig. 2.3 - OFDM block diagram: (a) transmitter; (b) receiver. ... 15

Fig. 2.4 - OFDM signal in the frequency domain. ... 16

Fig. 2.5 - Signal components from multipath channel and the FFT window. ... 17

Fig. 2.6 - OFDM and SC-FDMA block diagram: (a) transmitter; (b) receiver. ... 18

Fig. 2.7 - CE-OFDM block diagram: (a) transmitter; (b) receiver. ... 20

Fig. 2.8 - Saleh-Valenzuela channel response example. ... 24

Fig. 2.9 – Block diagram of a single-user system. ... 25

Fig. 2.10 - Diversity/multiplexing gains trade-off: (a) diversity gain equal to 4 and multiplexing gain equal to 1; (b) diversity gain equal to 2 and multiplexing gain equal to 2.. ... 26

Fig. 2.11 - IB-DFE block diagram. ... 29

Fig. 2.12 - Atmospheric absorption. ... 32

Fig. 2.13 - Radiation diagram: (a) SISO system; (b) MISO system. ... 34

Fig. 2.14 - Antenna Array configurations. ... 35

Fig. 2.15 - Patch antenna size (3GHz) Vs mmWave array antenna. ... 36

Fig. 2.16 - Promising architectures for mmWave mMIMO systems. ... 42

Fig. 2.17 - Hybrid analog/digital architecture. ... 42

Fig. 2.18 - Fully connected structure. ... 43

Fig. 2.19 - Sub-connected structure: (a) fixed subarray; (b) dynamic subarray. ... 44

Fig. 2.20 - Hybridly connected structure (fixed subarray)... 45

Fig. 2.21 - Phase shifter implementation (a) single; (b) double. ... 46

Fig. 2.22 - Receiver structure with 1-bit ADC. ... 46

Fig. 3.1 - Transmitter block diagram. ... 53

Fig. 3.2 - Receiver block diagram. ... 54

Fig. 3.3 - Performance of the proposed hybrid equalizer as function of the number of time slots (T) for scenario 2 and sparse precoders... 64

(20)

Fig. 3.4 - Performance of the proposed hybrid equalizer for scenario 1: (a) hybrid random precoders; (b) sparse precoders. ... 66 Fig. 3.5 - Performance of the proposed hybrid equalizer for scenario 2: (a) hybrid random precoders; (b) sparse precoders. ... 67 Fig. 3.6 - Performance of the proposed hybrid equalizer for scenario 3: (a) hybrid random precoders; (b) sparse precoders. ... 68 Fig. 3.7 - User terminal u block diagram. ... 70 Fig. 3.8 - Receiver block diagram. ... 71 Fig. 3.9 - Impact of the parameter T in the proposed hybrid equalizer for scenario 2: (a) BER as a function of Eb/N0; (b) BER for Eb/N0 = - 2 dB as a function of the block size T. ... 82

Fig. 3.10 - Performance comparison of the proposed hybrid equalizer for scenario 1 with: (a) the semi analytic BER approximation; (b) full-digital equalizer and the two-stage approach. ... 84 Fig. 3.11 - Performance comparison of the proposed hybrid equalizer for scenario 2 with: (a) the semi analytic BER approximation; (b) full-digital equalizer and the two-stage approach. ... 86 Fig. 3.12 - Performance comparison of the proposed hybrid equalizer for scenario 3 with: (a) the semi analytic BER approximation; (b) full-digital equalizer and the two-stage approach. ... 87 Fig. 3.13 - Hybrid Iterative Multiuser Equalizer for sub-connected architecture. ... 88 Fig. 3.14 - Performance of the proposed sub-connected hybrid multiuser equalizer: (a) for scenario 1.b; (b) comparison for scenario 1.b with a fully-connected approach. ... 97 Fig. 3.15 - Performance comparison of the proposed sub-connected hybrid multiuser equalizer with a fully-connected approach for: (a) scenario 2.b; (b) scenario 1.a. ... 99 Fig. 3.16 - Performance comparison of the proposed sub-connected hybrid multiuser equalizer for R = 2, 4 and 6 for: (a) scenario 1; (b) scenario 2. ... 100 Fig. 4.1 - General block diagram of the uth user terminal based on SC-FDMA. ... 105 Fig. 4.2 - Proposed receiver structure based on SC-FDMA. ... 106 Fig. 4.3 - Performance of the proposed hybrid iterative multi-user equalizer (Algorithm 4.2.1) for QPSK modulation: (a) NCSI precoder; (b) PCSI precoder. ... 118 Fig. 4.4 - Performance comparison between the Algorithm 4.1 and 4.2 for QPSK modulation: (a) NCSI precoder; (b) PCSI precoder. ... 120 Fig. 4.5 - Performance for the PCSI precoder and 16 QAM modulation: (a) Algorithm 4.1; (b) comparison between the Algorithm 4.1 and 4.2... 121 Fig. 4.6 - Proposed receiver structure based on SC-FDMA. ... 123 Fig. 4.7 - Analog part: (a) fully connected; (b) subconnected with fixed subarray; (c) subconnected with dynamic subarray. ... 124 Fig. 4.8 - Performance of the proposed dynamic hybrid equalizer for different numbers of quantization bits, with U =NrxRF =2, Nrx =32and R=16. ... 132

(21)

Fig. 4.9 - Simulated and theoretical performance of the proposed equalizer for subconnected architectures with dynamic subarray antennas, where RF 4

rx

U=N = and Nrx =64, i.e., 16

RF rx rx

R=N N = . ... 133

Fig. 4.10 - Simulated and theoretical performance for Eb N0 = −5dBof the proposed equalizer for subconnected architectures with dynamic subarray antennas, where U =NrxRF = and 4 Nrx =64, i.e.,

16 RF rx rx

R=N N = . ... 134

Fig. 4.11 - Performance comparison between the fully connected and sub-connected (fixed subarray) with the proposed equalizer for sub-connected architectures with dynamic subarray antennas, where: (a) RF 4

rx U=N = and N_rx =64, i.e., RF 16 rx rx R=N N = ; (b) RF 4 rx U=N = and N_rx =128, i.e., RF 32 rx rx R=N N = . ... 136

Fig. 4.12 - Performance comparison of the proposed equalizer for subconnected architectures with dynamic subarray antennas, where: (a) Nrx =64; (b) 4

RF rx

U=N = . ... 138 Fig. 4.13. Block diagram of the uth user terminal based on CE-OFDM. ... 140 Fig. 4.14. Proposed receiver structure based on CE-OFDM. ... 141 Fig. 4.15. Performance comparison of the proposed iterative hybrid equalizer with RF 8

rx

N =U= , and 32

rx

N = for different modulation indexes. ... 147

Fig. 4.16. Performance of the proposed iterative hybrid equalizer and semi-analytic BER approximation, with 8

RF rx

N =U = and N_rx=32. ... 148

Fig. 4.17. Performance comparison between the proposed iterative hybrid equalizer and full-digital equalizer, with: (a) NrxRF =U = and 8 Nrx =32; (b) 8

RF rx

N =U = and Nrx =64. ... 149

Fig. 4.18. Performance comparison of the proposed iterative hybrid equalizer with N_rx=32, for different number of users U =NrxRF. ... 150

Fig. 4.19. Performance comparison of the proposed iterative hybrid equalizer with NrxRF =U= , for 8

(22)

(23)

List of Tables

Table 2.1 - Attenuation of mmWave signals in different materials. ... 32 Table 2.2 - Path Loss. ... 36 Table 4.1 - Gap in dB between the equalizers at a target BER of 10−3 for the different architectures. ... 136 Table 4.2 - Simulation parameters. ... 146

(24)

(25)

List of Acronyms

1G 1st generation 2D Two Dimensional 2G 2nd generation 3D Three Dimensional 3G 3rd generation 4G 4th generation 5G 5th generation AA Antenna array

ADC Analog-to-digital converter

AMPS Advanced mobile phone system

AoA Angles of arrival

AoD Angles of departure

AWGN Additive white Gaussian noise

BER Bit-error-rate

BS Base station

CE-OFDM Constant envelope OFDM

CP Cyclic prefix

CSI Channel state information

DAC Digital-to-analog converter

DoF Degrees of freedom

CPMA Code modulated path sharing multi-antenna

DFT Discrete Fourier transform

EDGE Enhanced data rates for GSM evolution

EHF Extremely high frequency

eMBB Enhanced mobile broadband

(26)

E-UTRA Evolved UTRA

FDD Frequency division duplex

FFT Fast Fourier transform

GMSK Gaussian minimum shift keying

GPRS General packet radio system

GSM Global system for mobile communications

IB-DFE Iterative block decision feedback equalization

IC Interference cancellation

ICI Intercarrier interference

IDFT Inverse discrete Fourier transform

IFFT Inverse fast Fourier transform

IID Independent and identically distributed

IP Internet protocol

ISI Inter-symbol interference

LOS Line of sight

MIMO Multiple-input and multiple-output

MISO Multiple-input single-output

mMIMO Massive MIMO

MMSE Minimum mean square error

mMTC Massive machine type communications

mmWave Millimeter wave

M-QAM M-quadrature amplitude modulation

MRC Maximal ratio combining

MRT Maximum ratio transmission

MSE Mean square error

NCSI Non-channel state information

NLOS Non line of sight

(27)

OFDMA Orthogonal frequency-division multiple access

OMP Orthogonal matching pursuit

PA Power amplifier

PAPR Peak-to-average power ratio

PCSI Partial channel state information

PDP Power delay profile

QoS Quality of service

RF Radio frequency

RMS Root mean square

SC-FDMA Single-carrier frequency-division multiple access

SINR Signal to interference plus noise ratio

SISO Single-input single-output

SNR Signal-to-noise ratio

SoA State of the art

STBC Space-time block codes

STTTC Space-time turbo trellis codes

SVD Singular value decomposition

TCP Transport control protocol

TDD Time division duplex

ULA Uniform linear array

UMTS Universal mobile telecommunication system

UPA Uniform planar array

URLLC Ultra-reliable and low latency communications

UT User terminal

UTRA Universal terrestrial radio access

UTRAN UTRA network

(28)

(29)

Notation

Operator Description tr(.) Trace of a matrix * (.) Conjugate of a matrix (.)T Transpose of a matrix (.)H Hermitian of a matrix

{ }

1 1 1 l L l l l

α ₌− + Represents a L length sequence

diag( )a Diagonal matrix where the diagonal entries are equal to vector a

diag( )A Vector equal to the diagonal entries of the matrix A

1

[ _q]_{≤ ≤}_q _Q = a

a _a∈ℂQ Q1 2_{is the concatenation of vectors} Q2

q∈ a ℂ 1 1 [ _q]_{≤ ≤}_q _Q = A

A _A∈ℂQ Q1 2×L_{is the concatenation of matrices} Q2 L

q

×

∈

A ℂ

( , )n l

A The element of nth row and lth column of A

N

I Identity matrix N×N

p

e P

p∈

e ℂ is a P -length vector of zeros with the pth entry equal to one

\

Ω Λ Set of values from Ω , except the set of values from Λ

(30)

(31)

List of symbols

Symbol Description

d

H Delay-d MIMO channel matrix

k

H _{Frequency domain channel matrix at subcarrier k}

tx

a _{Normalized transmit array response vector}

rx

a Normalized receive array response vector

cl

N Number of clusters

ray

N Number of rays per cluster

T Time interval in which the channel remains constant

c

N Number of carriers

D Length of cyclic prefix

2

n

σ Power of channel noise

2

s

σ Power of each transmitted data stream

2

u

σ Power of each transmitted data stream of each user

s Data symbol

c Codeword built from data symbols

x Transmitted data

y _{Received data}

tx

N Number of transmit antennas

RF tx

N Number of transmit RF chains

s

N Number of streams

rx

N Number of receive antennas

RF rx

(32)

U Number of users

d

F Digital matrix of hybrid precoder

a

F Analog matrix of hybrid precoder

a

f Analog vector of precoder

a

W Analog matrix of hybrid equalizer

d

W Digital feedforward matrix of hybrid equalizer

d

B Digital feedback matrix of equalizer

fd

W Fully digital feedforward matrix of equalizer

fd

W Non-normalized version of fully digital feedforward matrix of equalizer

res

W Residue matrix

Rɶ Inter-symbol interference plus channel noise correlation matrix

Ψ Diagonal correlation matrix whose elements represent a measure of the

(33)

Chapter 1

Chapter 1 - Introduction

Introduction

This Chapter begins with an introduction about the evolution of mobile communication systems, from the first mobile phones to the current generation. After, the next generation is discussed. Namely, the technologies and frequency spectrum to be used, as well as the main obstacles. Following, and according to the motivation and objectives presented, the original contributions of this work are listed. Finally, the organization of this document is described.

1.1 – Evolution of cellular communication systems: From 1st to 4th

generation

Cellular communication technology has been developed over the past half-century with new capabilities and services to the end user. In addition to the new capabilities and services, the main differences over time are related to the data rate, the technology (for instance, analog or digital), processing techniques, among others. Currently, we can distinguish four generations of cellular communications already experienced: the 1st generation, the 2nd, 3rd and 4th (1G, 2G, 3G and 4G, respectively). Each generation lasted approximately a decade, beginning in the 80’s. This generations are briefly discussed next.

1980

Data rate:

2 kbps

Although the mobile radio telephone has appeared in the 50’s, the 1G cellular mobile radio networks appeared only in 80’s [1]. These cellular systems only provided speech services, using a separated narrowband frequency channel based on analog

(34)

technologies that allowed the speech services [2]. One cellular standard was the Advanced Mobile Phone System (AMPS), which used frequency modulation and frequency division multiple access (FDMA), with a one-way channel bandwidth of 30 kHz and a frequency band of 824 – 894 MHz, making a total of 832 channels [3].

1990

Data rate:

64 kbps

The development of the Global System for Mobile communications (GSM) standard led to the first 2G digital cellular system globally adopted in the 90’s [2]. The GSM is based on Time Division Multiple Access (TDMA), frequency division duplex (FDD) and Gaussian minimum shift keying (GMSK) modulation [2]. In addition to the digital signals for voice transmission, that has improved transmission quality, in 2G it is also possible to deliver text and picture messages [4]. 2.5 generation (2.5G) and 2.75 generation (2.75G) were not defined formally as wireless standards, however they are associated with the evolution of GSM. In 2.5G was defined the general packet radio system (GPRS) which can be used in all data services, as internet browsing, accessing wireless application protocol (WAP), short message service (SMS) and multimedia message system (MMS). In 2.75G was defined the Enhanced Data rates for GSM Evolution (EDGE). 2.5G/2.75G included already packet-switched services, namely the transport control protocol (TCP) and the Internet protocol (IP) [2].

2000

Data rate:

2 Mbps

The aim of 3G was to offer high speed data and it is based on GSM [4]. The 3G mobile system is the Universal Mobile Telecommunication System (UMTS) for Europe, while the American variant is the Code Division Multiple Access 2000

(35)

(CDMA 2000) [4]. For the UMTS, the main air interface is wideband CDMA, also known as universal terrestrial radio access (UTRA), where the UTRA network (UTRAN) works asynchronously and can be configured in the frequency division duplex (FDD) and time division duplex (TDD) modes [2]. In the CDMA 2000 case, the air interface is based on multiple narrowband CDMA carriers and the network of base stations (BSs) is synchronized [2]. 3G offers data services, internet services, access to television and video, video chatting, and global roaming [4].

2010

Data rate:

1 Gbps

4G offers the same features as the previous generation, but with additional services and higher data rate [5]. The aim of 4G is to achieve the intended Quality of Service (QoS) and data rates for several applications, namely voice and data services, Multimedia Messaging Service, video chat, mobile TV, high-definition TV content, Digital Video Broadcasting, wireless wideband access, among others [6]. The development of the standard Long Term Evolution (LTE) started in 2004 and became the 4G technology [2]. The first LTE mobile phone appeared in 2010. The air interface is the evolved UTRA (E-UTRA), where the E-UTRA network only requires phase synchronization for TDD mode and can operate in FDD and TDD modes [7]. For the downlink, the E-UTRA is based on the orthogonal frequency-division multiple access (OFDMA) while for the uplink is based on single-carrier frequency-division multiple access (SC-FDMA) [2].

1.2 – Future wireless communication systems

The deployment of a large number of antennas, together with the access to more bandwidth, has been considered an enabling technology for meeting the ever increasing demand of higher data rates in future wireless networks [8]. Therefore, massive multiple

(36)

input multiple output (mMIMO) and millimeter wave (mmWave) communications will be two of the keys enabling technologies for future wireless communication systems [9]-[11]. Small cells for ultra-dense networks are also one of the key solutions to increase capacity. These technologies are the three pillars that allow 5G [12], as we can see in the Fig. 1.1, to achieve the requirements for the three main usage scenarios: enhanced mobile broadband (eMBB) with a wide-area coverage and hotspots for a high capacity and seamless user experience, ultra-reliable and low latency communications (URLLC), and finally massive machine type communications (mMTC) with a very large coverage and number of connected low-cost devices employing a very long battery life [2].

Using the mmWave frequency spectrum, localized in 30-300 GHz band and corresponding to wavelength 1 – 10 mm, several tens of GHz could become available for future wireless systems [13], offering multi Gb/s, which can support many applications such as short-range communications, vehicular networks, and wireless backhauling [12]. Furthermore, due to the high attenuation with the distance, as it can be seen from Fig. 1.1, mmWave enables the use of small-cells based networks because the interference between cells is reduced.

On the other hand, mMIMO scale up MIMO by orders of magnitude compared to the conventional MIMO approaches [14] and it is capable of improving the bandwidth efficiency or the reliability by improving the multiplexing gains or diversity gains as a result of the inherent high degrees of freedom (DoF) [15]. This one is suitable to implement a high spatial reuse since narrow beams can be obtained with the large number of antennas, which allows to reduce the multi-user interference by directing energy to desired terminals only, boosting the overall ultra-dense network capacity. Moreover, mMIMO is robust against fading, the failure of antenna units and it reduces the constraints on accuracy and linearity of each individual amplifier [16]. When deployed in the small-cell mmWave context, the costs and power are considerably reduced, since low-cost low-power components can be used, as well as expensive and bulky components as large coaxial, and high-power radio frequency (RF) amplifiers at the front-end can be eliminated [12].

(37)

Fig. 1.1 - Keys and scenarios for 5G systems.

1.3 – Motivations and objectives

MmWave frequencies, because of their much smaller wavelength, enable the exploitation of new spatial processing techniques, such as adaptive beamforming and mMIMO, where it is allowed packing more antennas in the same volume compared to current microwave communication systems [17]. Therefore, the combination of mMIMO with mmWave is highly attractive because it was shown that mmWave systems, combined with further gains via beamforming and spatial multiplexing from multi-element antenna arrays, can offer more than an order of magnitude increase in capacity over the current state of the art (SoA) 4G cellular networks at current cell densities [18] and overcompensate the propagation difficulties of mmWave communications [19]. However, mmWave mMIMO also offers more correlated channels, since the multipath diversity effects are much lower in mmWave mMIMO channels [20][21], and thus it is needed to exploit new and efficient beamforming techniques and spatial multiplexing for both the transmitter and the receiver sides. Moreover, the power consumption and high cost of analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) mixers or power amplifiers for mmWave, make it impractical to have one fully dedicated RF chain for each transmit and receive antenna as in sub-6 GHz MIMO systems [22]. Therefore, the hardware limitations make it necessary to design techniques different from the ones that were adopted for sub-6 GHz counter-parts [19].

m m W a v e C o m m u n ic a ti o n M a s s iv e M IM O U lt ra -D e n s e N e tw o rk

5G

Enhanced mobile broadband

Ultra-reliable and low latency communications Massive machine type

communications Lower interference Short-range communication Higher spatial reuse Higher capacity

Smaller antenna size

(38)

A simple approach is the employ of fully analog beamforming techniques using only phase shifters to overcome the hardware limitations, allowing low complexity implementations [23]. However, the performance of the pure analog signal processing approach is limited since it is usually used only for single-stream transmission [24]. To overcome the performance limitations, the solution is the use of hybrid analog-digital architectures, where part of signal processing is done at the analog domain and a reduced-complexity processing is left to the digital domain [24][25]. Nevertheless, the processing performed on conventional MIMO systems cannot be used in these architectures, so it becomes absolutely crucial to develop new algorithms.

Another important aspect in a communication system is the adopted modulation technique. The orthogonal frequency division multiplexing (OFDM) is known as an efficient technique to mitigate the effects of inter-symbol interference in frequency selective channels [26]. Combining OFDM with MIMO significantly reduces receiver complexity in wireless wideband systems, thus making it a competitive choice for future wideband wireless communication systems and it has already been adopted in some high rate wireless communications standards, namely for the downlink [27]. The main drawback of OFDM modulations is the high signal fluctuations that lead to large PAPR [28]. This causes some challenges to the power amplifier (PA) design since OFDM is sensitive to nonlinear distortions caused by PA [29]. The amplifier must stay in the linear area, using extra power backoff in order to prevent problems in the output signal. However, the use of higher back-off leads to a reduced PA efficiency or a smaller output power [30]. In this context, SC-FDMA with a lower PAPR than OFDM and constant envelope OFDM (CE-OFDM) with PAPR = 0 dB can be more interesting options for practical systems. For this reason, these two modulation techniques are explored in this research work.

Finally, techniques for the mmWave mMIMO systems should also contemplate the interference. This is an issue that should be carefully managed. Beamforming techniques can be used to separate different links without wasting resources and this can be especially effective on mmWave communications due to massive antenna implementations [8]. Moreover, the linear equalization is not the most efficient due to residual intercarrier interference (ICI). Therefore, nonlinear equalizers were taken into consideration to efficiently separate the spatial streams and/or remove the multiuser interference in the current MIMO based networks [31]. The Iterative Block Decision-Feedback Equalizer

(39)

(IB-DFE) approach are one of the most promising nonlinear equalization schemes [31]. IB-DFE can be especially efficient in mMIMO systems, because of the inherent characteristics of this system. This topic is explored in this research work.

Therefore, in this work we design efficient hybrid precoding and iterative equalizers for both narrowband and wideband mmWave mMIMO systems, employing SC-FDMA and CE-OFDM modulations. The proposed algorithms are designed for three kinds of hybrid architectures: 1) fully connected, where each RF chain is connected to all antennas; 2) fixed subconnected, where each RF chain is connected only to a fixed subset of antennas and 3) dynamically subconnected, where each RF chain is connected to a subset of antennas selected dynamically following a given criterion.

1.4 – Original contributions

As discussed, mmWave mMIMO brings new major challenges that prevent a direct plug and play of the precoding and detection based solutions developed for conventional MIMO systems. Therefore, in this PhD work are developed novel efficient analog-digital transmit and receive schemes for mmWave mMIMO systems. Specifically, the main contributions include:

 Design of schemes for narrowband hybrid mmWave mMIMO systems. These schemes include:

• A novel iterative single-user space-time equalizer for fully connected hybrid systems [C5],[C7].

• Extension of the previous single-user solutions to the multiuser scenario [C4],[C6],[J5].

• A novel iterative multiuser space-time equalizer for fixed sub-connected hybrid systems, with the objective of developing a more interesting option in terms of power consumption and hardware cost [J4].

 Design of schemes for wideband hybrid mmWave mMIMO systems. These schemes include:

(40)

• A novel hybrid precoder based on average AoD knowledge at user terminals. This finding was reported for single stream case [C1],[C3],[J1], [J2], and for multi-stream case [C2].

• A novel iterative multiuser space-frequency equalizer for fully connected hybrid systems with SC-FDMA modulation [C2], [J1], and CE-OFDM [C1],[J2]. • The approach designed for SC-FDMA was also extended for fixed

sub-connected hybrid systems [C3].

• A novel iterative multiuser space-frequency equalizer specifically designed for dynamic sub-connected hybrid systems [J3].

The work has produced a number of scientific publications: 5 journals and 9 conference papers listed below.

Papers in journals

[J1] R. Magueta, D. Castanheira, P. Pedrosa, A. Silva, R. Dinis and A. Gameiro, "Iterative Analog-Digital Multi-User Equalizer for Wideband Millimeter Wave Massive MIMO Systems", Sensors, MDPI, Vol. 20, No. 2, pp. 575-595, Jan. 2020.

[J2] R. Magueta, S. Teodoro, D. Castanheira, A. Silva, R. Dinis and A. Gameiro, "Multiuser Equalizer for Hybrid Massive MIMO mmWave CE-OFDM Systems",

Applied Sciences, Vol. 9, No. 16, pp. 1-18, Aug. 2019.

[J3] R. Magueta, D. Castanheira, A. Silva, R. Dinis and A. Gameiro, "Hybrid Multi-User Equalizer for Massive MIMO Millimeter-Wave Dynamic Subconnected Architecture", IEEE Access, Vol. 7, pp. 79017-79029, June 2019.

[J4] R. Magueta, V. Mendes, D. Castanheira, A. Silva, R. Dinis, and A. Gameiro, “Iterative Multiuser Equalization for Subconnected Hybrid mmWave Massive MIMO Architecture,” Wireless Communications and Mobile Computing, vol. 2017, pp. 1-13, Dec. 2017.

(41)

[J5] R. Magueta, D. Castanheira, A. Silva, R. Dinis and A. Gameiro, "Hybrid Iterative Space-Time Equalization for Multi-User mmW Massive MIMO Systems", IEEE

Transactions on Communications, Vol. 65, No. 2, pp. 608 - 620, Feb. 2017.

Papers in proceedings of scientific meetings

[C1] R. Magueta, R. Enes, S. Teodoro, A. Silva, D. Castanheira, R. Dinis, and A. Gameiro, "Hybrid Nonlinear Multiuser Equalizer for mmWave Massive MIMO CE-OFDM Systems," IEEE Symposium on Personal, Indoor and Mobile Radio Communications

(PIMRC), Istanbul, Turkey, Sep. 2019.

[C2] R. Magueta, D. Castanheira, A. Silva, R. Dinis, and A. Gameiro, "Two-Step Analog-Digital Multiuser Equalizer for hybrid precoded mmWave Communications," IEEE

Global Communications Conference (GLOBECOM), Abu Dhabi, UAE, Dec. 2018. [C3] R. Magueta, D. Castanheira, A. Silva, R. Dinis, and A. Gameiro, "Two-Step Hybrid

Multiuser Equalizer for Sub-Connected mmWave Massive MIMO SC-FDMA Systems," European Signal Processing Conference (EUSIPCO), Rome, Italy, Sep. 2018.

[C4] R. Magueta, D. Castanheira, A. Silva, R. Dinis, and A. Gameiro, "Nonlinear Equalizer for Multi-User Hybrid mmW Massive MIMO Systems", IEEE 85th

Vehicular Technology Conference, Sydney, Australia, June, 2017.

[C5] R. Magueta, D. Castanheira, A. Silva, R. Dinis, and A. Gameiro, "Transmit Beamforming Strategies with Iterative Equalization for Hybrid mmW Systems", The

Second International Conference on Advances in Signal, Image and Video Processing, Barcelona, Spain, May, 2017.

[C6] R. Magueta, D. Castanheira, A. Silva, R. Dinis, and A. Gameiro, "Two-Stage Space-Time Receiver Structure for Multi-user Hybrid mmW Massive MIMO Systems",

IEEE Conference on Standards for Communications and Networking, Berlin, Germany, Oct. 2016.

(42)

[C7] R. Magueta, D. Castanheira, A. Silva, R. Dinis, and A. Gameiro, "Non Linear Space-Time Equalizer for Single-User Hybrid mmWave Massive MIMO Systems", 8th

International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), Lisbon, Portugal, Oct. 2016.

[C8] R. Magueta, D. Castanheira, A. Silva, R. Dinis and A. Gameiro, "Iterative Space-Frequency Equalizer for CE-OFDM mmW based Systems", in Proc. of IEEE

Symposium on Computers and Communications, Messina, Italy, June 2016.

[C9] Roberto Magueta, Adão Silva, Rui Dinis and Atílio Gameiro, "Iterative Frequency Domain Equalizer for MIMO CE-OFDM based Systems", International Conference

on Telecommunications - ConTEL 2015, Austria, July 2015.

1.5 – Thesis organization

This thesis is organized into five chapters, which include the introduction, an overview of multicarrier, conventional MIMO and mmWave and mMIMO systems, the description of the proposed narrowband and wideband techniques, the conclusion and future work. The remaining of the thesis is organized as follows:

 Chapter 2 starts by presenting a brief overview about the modulation schemes used in this work, followed by an overview on conventional sub-6 GHz MIMO systems, whose subjects are the conventional wireless channel models, MIMO systems and interference mitigation techniques. After that, a brief review of the key future wireless systems concepts is provided, namely mmWave, mMIMO and the potentialities of the combination of both. Then follows the description of clustered narrowband and wideband channel models for mmWave mMIMO characterized by a sparse-scattering structure. To conclude the Chapter 2, the hybrid full- and sub-connected architectures, which are specifically tailored for mmWave mMIMO systems, are presented.

 In Chapter 3, the proposed iterative single-user space-time equalizer for hybrid full-connected systems is described. First, a multi-stream transmission is considered, and the purpose of this design is to develop an efficient technique to separate the spatial

(43)

streams. Second, the previous proposal is extended for the multiuser case, since it is expected from the wireless communication systems to have several terminals sharing the same resources. Finally, the techniques developed are extended for a hybrid sub-connected architecture.

 In Chapter 4 the proposed solutions for wideband system, employing SC-FDMA and CE-OFDM modulations are presented. First, it is proposed a hybrid low complexity precoder and an iterative multiuser space-frequency equalizer for hybrid full-connected architectures. After that, a sub-full-connected (fixed and dynamic variants) solution was also developed. All the previous solutions were designed for SC-FDMA systems. Finally, an iterative space-frequency equalizer for hybrid full-connected architectures, with a constant envelope modulation (the CE-OFDM) was designed to solve the problem of PAPR in the mmWave mMIMO based systems.

 Chapter 5 concludes this thesis, summarizing the main achieved results and presenting some possible topics for future work.

(44)

(45)

Chapter 2

Chapter 2 - Background on multicarrier, MIMO and mmWave mMIMO systems

Background on multicarrier, MIMO

and mmWave mMIMO systems

This Chapter begins by presenting some modulation schemes such as OFDM, SC-FDMA and CE-OFDM. Then, a brief outline regarding the conventional MIMO is presented, followed by an overview of mmWave mMIMO systems. In the Section of mmWave mMIMO systems, beyond the general features of these systems, channel models to represent the features of mmWave mMIMO channels are addressed, since they are needed in the next Chapters to design and evaluated the proposed hybrid algorithms. Finally, alternative architectures to allow the best trade-off between the performance and power/costs requirements are also presented.

2.1 – Modulation schemes

In this Section we start by presenting the OFDM modulation, which is a very popular multicarrier technique that has been used within current wireless technologies. After that, we address the SC-FDMA, currently used in the LTE standard for the uplink. Both schemes are also proposed for 5G. Finally, we address the CE-OFDM that can be used in the future wireless systems, since it allows low-cost and highly efficient power amplification.

(46)

2.1.1 – OFDM

Single and multicarrier are two types of transmission. Being the best choice between one and the other dependent mainly of the coherence time/bandwidth of channel and the PAPR problem. The large data bandwidth of single carrier systems implies that the channel is only considered flat when the coherence bandwidth is also large, i.e., higher than the data bandwidth. This is something unusual to happen. Therefore, a multicarrier system approach can be used where the data signal is divided into different sub-streams that are sent each one by a different subcarrier. Then, the data rate of each sub-stream is lower than the initial data rate, occupying each one a lower bandwidth, as we can see in Fig. 2.1, when compared with the Fig. 2.2, and consequently the respective sub-channel can be considered flat.

Fig. 2.1 - Allocation of data symbols for multi carrier transmission.

Fig. 2.2 - Allocation of data symbols for single carrier transmission.

The best-known multicarrier technique is the OFDM, which has the advantage over single carrier systems of dealing with severe channel conditions, such as narrowband interference and frequency-selective fading due to multipath, without a complex equalizer. The main problem of OFDM is the large PAPR, which requires the use of power amplifiers with a very high linear range to avoid signal distortions, which make the system performance lower [37].

1

s

₂

s

₃ Frequency A m p li tu d e Time slot 1 Frequency A m p li tu d e Time slot 2 Frequency A m p li tu d e Time slot 3 1

s

₂

s

₃

s

₁

s

₂

s

₃ 1

s

Frequency A m p li tu d e Time slot 1 2

s

Frequency A m p li tu d e Time slot 2 3

s

Frequency A m p li tu d e Time slot 3

(47)

The block diagram of the OFDM is presented in Fig. 2.3. At the transmitter, a bit stream

is modulated in data symbols that are mapped into the OFDM frame. Then a Nc-point IFFT

is applied and finally the cyclic prefix (CP) is added. At the receiver, the CP is removed, and

a Nc-point FFT is performed. After that, the equalizer in the infrequence domain is applied

to remove the effects of channel, followed by the de-mapping operation and finally the data demodulation is done.

(a)

(b)

Fig. 2.3 - OFDM block diagram: (a) transmitter; (b) receiver.

When the original data stream with bandwidth B , is modulated by the subcarriers

1

,..., ,...,

c

o k N

f f f ₋ , where N_c is the number of subcarriers used, the spacing between

subcarriers is , c B f N ∆ = (2.1)

and the OFDM symbol duration in a subcarrier is given by 1 . c OFDM N T f B = = ∆ (2.2)

As we can verify in (2.2), TOFDM >1 /B, the delay spread is a shorter fraction of the symbol

period, which leads to a channel less sensitive to fading, channel distortion and ISI. The

orthogonality between subcarriers requires that ∆f must be a multiple of 1

OFDM T− , and Ant. 1 Ant. Ntx Data Mod. Bit stream S / P Subcarrier mapping P / S … _Add CP Nc -point IFFT … … … Ant. 1 Ant. Nrx Equalizer S / P Nc-point FFT … … Delete CP … P / S Data Demod. Subcarrier de-mapping … … Bit stream

(48)

typically this multiple is one, as showed in (2.2). This condition arises because the OFDM symbol pulse is shaped by a square wave in the time domain, which results in a sinc in the

frequency domain [38]. Therefore, as seen in Fig. 2.4, when we choose a ∆f multiple of

1

OFDM

T− , the nulls in the spectrum of one subcarrier line up with the peaks of the adjacent

subcarriers [39]. In this way, we have a good spectral efficiency and no interference, allowing to recover the original signal.

Fig. 2.4 - OFDM signal in the frequency domain.

The received signal is

1 2 / 2 0 ( ) Re rect( / ) , c OFDM c N j kt T j f t k OFDM k r t s t T e π e π − =   = _ _ 



 (2.3)

where sk∈ℂ is a data symbol from a given constellation, and fc is the RF carrier. The

function rect(.) is the rectangular pulse shaping function. Removing the RF carrier, we

obtain the baseband signal, given by

1 2 2 / 0 ( ) ( ) . c c OFDM N j f t j kt T k k c t r t e π s e π − − = = =



(2.4)

Finally, if we sample the signal c t( ) at a rate N_c/T_OFDM , we obtain

(

)

1 2 0 / , , 0,..., 1, k c f N _j _n B n OFDM c k k c k c c nT N s e π f k f n N   − _ _   = = =



= ∆ = − (2.5) Frequency f_k-5 f f_k-4 f f_k-3 f f_k-2 f f_k- f f_k f_k+ f f_k+2 f f_k+3 f f_k+4 f f_k+5 f

(49)

which coincides with the inverse discrete Fourier transform (IDFT), i.e., c_n =IDFT

( )

s_k . Therefore, to demodulate the data at receiver side, it is only needed to apply the discrete Fourier transform (DFT), which may be efficiently calculated using the fast Fourier transform (FFT) algorithm.

As mentioned above, a CP is added to the transmitted signal. The CP is a copy of the last part of OFDM symbol, which is attached in the beginning of symbol, and it makes the channel circular. The CP is used because in a time-dispersive channel, the OFDM symbol can lose their orthogonality which causes ISI [35]. This CP should have a duration higher than the maximum delay spread of the multipath channel (Fig. 2.5 (a)), otherwise we will have ISI, as we can see in Fig. 2.5 (b). Additionally, the OFDM symbol duration increases when the CP duration also increases, then we cannot increase the CP duration as much as we want or then the transmission rate is reduced. Finally, to avoid the ICI, we need the

spacing between subcarriers, ∆f , tobe much higher than the maximum Doppler shift [36].

These considerations about CP are also valid for the modulation schemes (SC-FDMA and CE-OFDM) presented next.

(a) (b)

Fig. 2.5 - Signal components from multipath channel and the FFT window.

2.1.2 – SC-FDMA

SC-FDMA, a modified form of OFDM, is a promising solution technique for high data rate uplink communications systems. When compared with OFDM, SC-FDMA has similar throughput and essentially the same overall complexity. The main advantage of SC-FDMA is the PAPR, which is lower than the PAPR of OFDM signals [32]. SC-FDMA has been adopted as the uplink multiple access scheme in LTE, or E-UTRA [33] and will be used in the 5G systems. As mentioned, SC-FDMA is an important option due to low PAPR, which benefits the user terminal (UT) relative to transmit power efficiency and reduced cost of the

CP CP CP CP CP CP Optimal FFT window (not unique) CP CP CP CP CP CP FFT window ISI

(50)

power amplifier. The SC-FDMA block diagram for the transmitter and receiver is shown in Fig. 2.6 [34]. As we can see, the SC-FDMA and OFDM shared several blocks, which facilitates for their practical implementations.

(a)

(b)

Fig. 2.6 - OFDM and SC-FDMA block diagram: (a) transmitter; (b) receiver.

Starting by the transmitter, firstly a bit stream is modulated in data symbols. After that, a set of S-point FFTs are applied, and a mapping procedure is performed, where the output is

mapped in N_c subcarriers. Typically, this mapping procedure can be done sequentially, or

distributed. Then, a Nc-point IFFT is applied and finally the CP is added. At the receiver, the

CP is removed and a Nc-point FFT is applied. After that, an equalizer is used in frequency

domain, in order to remove the effects of channel. Then, the de-mapping procedure is done and, before data demodulation, the S-points IFFT is performed.

Since in this PhD work, we are considering only the uplink direction, the designs presented in Chapter 4 for wideband channels employ the SC-FDMA modulation.

Ant. 1 Ant. Ntx Data Mod. Bit stream S / P S-point FFT Subcarrier mapping P / S … … S-point FFT … … … _Add CP Nc -point IFFT … … …

Legend: OFDM + SC-FDMA

Ant. 1 Ant. Nrx Equalizer S / P Nc-point FFT … … Delete CP S-point IFFT … … P / S Data Demod. Subcarrier de-mapping … … … S-point IFFT … … Bit stream

(51)

2.1.3 – CE-OFDM

As mentioned previously, the OFDM is an efficient technique to mitigate the effects of ISI in frequency selective channels [26]. However, the main drawback of OFDM modulations is the high signal fluctuations that lead to large PAPR [28]. This causes some challenges to the PA design since OFDM is sensitive to nonlinear distortions caused by PA [29]. The amplifier must stay in the linear area with the use of extra power back-off in order to prevent problems to the output signal. Still, the use of additional back-off leads to a reduced PA efficiency or a smaller output power [30]. As discussed in [40], efficient PA is a critical issue for mmWave based wireless systems. In this case it would be desirable to employ highly efficient amplifiers, such as class D, E or F amplifiers [41], which are strongly nonlinear and, therefore, only suitable to signals with constant or quasi-constant envelope. Nevertheless, even when PAPR-reducing techniques are employed, the resulting signals still require quasi-linear amplifiers (although with smaller backoff) [42].

CE-OFDM is a promising modulation technique for mmWave based wireless communications [17], since it allows low-cost and highly efficient power amplification based on strongly nonlinear amplifiers [43],[44]. Basically, CE-OFDM transforms the high PAPR OFDM signal in a constant envelope signal, i.e., with 0dB PAPR, suited for efficient amplification. CE-OFDM also shares many of the same functional blocks of standard OFDM, as we can see in Fig. 2.7, and therefore it can provide an additional CE-OFDM mode with relative ease [45]. As discussed in [45], CE-OFDM exploits the multipath diversity due to frequency spreading of the data symbols, contrarily to uncoded OFDM. Additionally, it was shown in [46] that CE-OFDM compares favorably with OFDM when the impact of nonlinear power amplification and power backoff is taken into account.

(a) Ant. 1 Ant. Ntx Data Mod. Bit stream S / P Symmetric and zero-padding P / S … … Add CP Nc -point IFFT … Phase … Modulator { } 1 c N k k z = { } 1 L k k s = { } 1 c N t t z = { } 1 c N t t c =

(52)

(b)

Fig. 2.7 - CE-OFDM block diagram: (a) transmitter; (b) receiver.

For the transmitter, as we can see in the block diagram of Fig. 2.7 (a), the generated bits from the data source are modulated for instance in a QAM format, obtaining a sequence of

L symbols,

{ }

_k L₁

k

s ₌ . Then, the Hermitian symmetric and zero-padding block is applied,

resulting in a sequence of N_c =2L+N_zp+ symbols, 2

{ }

_,

1

c

N u k _k

z

= , with a structure given by

{ }

* * 1 1 1 {0, ,..., , 0,..., 0 , 0, ,..., }, c zp L L N k k N z s s s s = = (2.6)

where the Nzp zeros are used to achieve the effect of oversampling of the time domain

sequence, whose oversampling factor is given byN_os =N_c/

(

N_c−N_zp

)

. An IFFT is applied,

and due to the structure of (2.6), the obtained sequence,

{ }

Nc₁

t t

z ₌ , is only composed by real

values, i.e., z_t∈ ℝ. After that, the phase modulator is applied, whose output, c_t , is given by

(

)

exp 2 ,

t t

c = A j πhz (2.7)

where A is the signal amplitude of c_t, and h is the modulation index. To conclude, the CP

is added.

At receiver side, as we can see in Fig. 2.7 (b), first, the CP is removed and then the

equalizer is applied in the frequency domain, obtaining in the time domain,

{ }

Nc₁

t _t

cɶ ₌ , that is an

estimated of transmitted sequence

{ }

Nc₁

t t

c ₌ . After that, it is performed the phase demodulation,

where from (2.7), we can use the arctangent function to obtain

{ }

1

c

N t _t

zɶ ₌ . After to apply the FFT

to

{ }

Nc₁

t t

zɶ ₌ , we obtain

{ }

Nc₁

k k

zɶ ₌ , with the structure (2.6), up to a noise. Then, the estimated L

data symbols are selected,

{ }

1

L k _k

sɶ ₌ , and finally the data demodulation is performed.

Ant. 1 Ant. Nrx Nc-point FFT + Equalizer + Nc-point IFFT S / P … Delete CP P / S Data Demod. Select data … Bit stream Phase Demodulator … S / P Nc-point FFT … … P / S { } 1 c N t t cɶ ₌ { }N₁c t t zɶ ₌ _{{ }} 1 c N k k zɶ ₌ { }L₁ k k s = ɶ

Hybrid precoding and equalizer techniques for mmWave and massive MIMO based wireless systems

Roberto Louro Magueta

Técnicas híbridas de pré-codificação e equalização

para sistemas sem fios baseados na banda das

ondas milimétricas e MIMO massivo

Hybrid precoding and equalizer techniques for

mmWave and massive MIMO based wireless

systems

Roberto Louro Magueta

Técnicas híbridas de pré-codificação e equalização

para sistemas sem fios baseados na banda das

ondas milimétricas e MIMO massivo

Hybrid precoding and equalizer techniques for

mmWave and massive MIMO based wireless

systems

Contents

List of Figures

List of Tables

List of Acronyms

Notation

{ }

List of symbols

Chapter 1

Introduction

1.1 – Evolution of cellular communication systems: From 1st to 4th

generation

1.2 – Future wireless communication systems

1.3 – Motivations and objectives

5G

1.4 – Original contributions

1.5 – Thesis organization

Chapter 2

Background on multicarrier, MIMO

and mmWave mMIMO systems

2.1 – Modulation schemes

s

s

s

s

s

s

s

s

s

s

s

s





(

)



( )

{ }

{ }

{ }

(

)

{ }

(

)

{ }

{ }

{ }

{ }

{ }

{ }