MULTI DIMENSIONAL SIGNAL PROCESSING IN BROADBAND MULTIUSER MOBILE COMMUNICATIONS

Subjects of the thesis - Signal-to-interference ratio SIR analysis for orthogonal frequency-division tiplexing OFDM transmission in the presence of carrier frequency offset, phase noise

MINISTRY OF EDUCATION AND TRAINING

THE UNIVERSITY OF DANANG

NGUYEN DUY NHAT VIEN

MULTI-DIMENSIONAL SIGNAL PROCESSING IN BROADBAND

This thesis has been finished at:

THE UNIVERSITY OF DANANG

Supervisor:

1 Associate Prof., Dr Tang Tan Chien,

2 Associate Prof., Dr Nguyen Le Hung

Examiner 1:

Examiner 2:

Examiner 3:

The thesis submitted for a defense in front of the Thesis Assessment Committee

of The Danang University

At Room No:

At 2016

The thesis is available at:

1 The National Library

2 The Information Resources Center, The University of Danang

1

-Introduction

In recent years, the next generation of wireless technologies are facing the long termchallenge to properly address the resource system limitations with the growing demand onservices, high data rate, fast mobility and wide coverage There is a traceoff between datarate and movement speed of users For high speed systems, the data-rate of users is lim-ited due to the complicated error detection and correction schemes which are required tofight against the fast fading and the transmission impairments Therefore, this thesis en-titled Multi-dimensional signal processing in broadband multiuser mobile communicationsaims to improve the data rate and the movement speed of the users for high-bandwidthapplications in the next generation wireless networks

Objectives of the thesis

- Propose a channel estimation algorithm which efficiently works for high-speedmovement users in full-duplex communication systems

- Propose algorithms for interference management to simultaneously improve thesum-rate and the coverage for multi-user wireless communication systems

Subjects of the thesis

- Signal-to-interference ratio (SIR) analysis for orthogonal frequency-division tiplexing (OFDM) transmission in the presence of carrier frequency offset, phase noise anddoubly selective fading

mul Fast fading channel estimation in fullmul duplex MIMOmul OFDM systems

- Pre- and post-coding matrix design for management interference and capacityoptimization

Scopes of the thesis

The effects of phase noise, carrier frequency, offset and fast fading; estimation niques; pre/post-coding; power allocation techniques in the next generation of wirelesscommunication systems

tech-Methods of the thesis - Combined method between analysis and Monte-Carlosimulation based on computer - Analytical method for modeling signals and systems, andresolving convex optimization problems under the constraints of realistic system conditions

- Monte-Carlo simulation method for analyzing the quality of the system using the proposedalgorithms Main system quality parameters include sum-rate, MSE, BER, SIR, and soon

Novelty of the thesis

- The thesis has derived signal-to-interference ratio (SIR) formula for time-variantchannels of OFDM transmission systems in the presence of carrier frequency offset andphase noise

- The thesis has developed channel estimation algorithms for MIMO-OFDM

full 2 full

-duplex transmission systems

- The thesis has designed pre/post-coding matrices of multi-hop multi-user nications

commu The dissertation has proposed algorithms for interference management for multicommu cell broadcast system in the absence of perfect channel state information

multi Structure of the thesis

Chapter 1: Overview of wireless communication systems In this chapter, theoverview of wireless communication systems is presented, including important factorsinfluencing the radio signal propagation Motivation of the thesis is given after acomprehensive literature review on the fields

Chapter 2: Multi-dimensional signal processing in mobile communications Inthis chapter, principles of multi-dimensional signal processing for mobile communica-tions such as OFDM, MIMO, estimation techniques, full-duplex transmissions and so

on are present Theoretical SIR expressions for the time-variant channel are developed

in the presence of phase noise and carrier frequency offset An estimation algorithmwhich is useful for high mobility full-duplex communication systems is also proposed

in this chapter

Chapter 3: Capacity improvement for the multi-user multi-hop mobile munication systems In this chapter, a method to enhance the capacity of multi-usermulti-hop wireless communication systems is proposed by designing pre/post-codingmatrices

com-Chapter 4: Interference management for multi-cell wireless networks Issues ofpre- and post-coding designs for multi-cell wireless networks are studied to proposealgorithms for managing both inter-user interference (IUI) and inter-cell interference(ICI) The interference management is investigated under mean square error (MSE)criterion, especially in the absence of perfect channel state information (CSI) Thesimulated results show a simultaneous improvement of the sum-rate and the coveragefor multi-cell multi-user transmissions

Conclusions and Outlook

3

systems

1.1 Introduction

1.2 Evolution of Mobile Communications

1.3 Mobile commnucation system

1.4 Wireless channel

1.5 Literature review

Recently, orthogonal frequency division multiplexing (OFDM) has been recognized

as a promising solution to facilitate the explosive growth in broadband data traffic of less multimedia services [74] However, the superior advantages of OFDM only exist underthe condition of perfect synchronization and quasi-static fading channel [73] In particular,synchronization impairments (e.g., CFO and PHN) give rise to inter-carrier interference(ICI) that would significantly degrade the performance of OFDM transmissions [24], [87]

wire-In addition, the presence of high-speed moving subscribers (in 4G mobile networks) causestime-selective channel response that also leads to ICI in OFDM systems [47] In the liter-ature, most of existing studies consider one or two of these channel impairments in systemanalysis In particular, the CFO effect on OFDM systems has been extensively studied in[24] while the investigation of phase noise has been addressed in [87] Besides imperfectsynchronization conditions, the effect of time-selective channels has been considered in[47], [63] Combined time-selective fading and phase noise effects on OFDM systems havebeen analyzed in [100] In addition, the effect of CFO and time-selective channels in SIRanalysis has been well documented in [7], [103] while the impacts of CFO and phase noisehave been investigated in [58]

The problem of channel estimation has been intensively studied in OFDM systems[74], [20] In particular, numerous blind or pilot-aided channel estimation techniques havebeen proposed for various OFDM transmission models ranging from single-cell, single-user, single-hop, single-antenna systems to multicell, multiuser, multihop, multi-antennanetworks [88] However, most of the existing channel estimation studies have consideredhalf-duplex wireless systems where signal transmission and reception occupy two differenttime or frequency slots [74], [88]

Recently, full-duplex transmission has appeared as a promising candidate for thenext generation of wireless communications [101] Using the full-duplex principle, bothsignal transmission and reception can simultaneously use the same frequency band andthus increasing the system spectral efficiency up to two times [35] However, using thefull-duplex principle produces strong self-interference signals at receive antennas [35] Infull-duplex systems, self-interference cancellation and coherent signal detection require theuse of channel state information (CSI) So far, the problem of CSI acquisition in full-duplex

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-systems has not received much attention in the literature More recently, [52] and [53] hasdevelop ML-based channel estimation algorithms for self-interference cancellation in full-duplex MIMO-OFDM systems over quasi-static fading channels (i.e., under a block-fadingchannel assumption)

Multiple-input multiple-output (MIMO) communication techniques have been animportant area of focus for next-generation wireless systems because of their potential forhigh capacity, increased diversity, and interference suppression [18] Recent informationtheoretic studies have proved that dirty paper coding (DPC) achieves the capacity region

of the MIMO [85] The power allocation technique to achieve optimal capacity is proposed

in [31], [39] Precoding is a generalization of beamforming to support multi-stream mission in MIMO wireless communication systems Block diagonalization (BD) precodinghas proposed in [72] and singular value decomposition (SVD) precoding has proposed [50]

trans-One-way relaying has been intensively studied in wireless communications to extendcell coverage area and to gain spatial diversity [42] However, the benefits of using one-wayrelay transmission come at the cost of reduced spectrum efficiency In particular, one-wayrelaying needs four time slots for one round of information exchange between two sourcenodes in a multihop network [61], [55] To avoid the spectrum efficiency loss of one-wayrelaying, two-way relay communications has been proposed for reducing the number oftime slots from four to two in the information exchange round [45], [99]

To further enhance the, space division multiple access (SDMA) transmission hasbeen leveraged in two-way relay network [32, 98] As a result, the SDMA-based multiusertransmission can significantly boost the capacity of the two-way relay network [59]

In mobile communications systems, universal frequency-reuse (multicell) sion has been extensively employed to enhance system-wide spectral efficiency However,the benefit of multicell transmissions comes at the price of inter-cell interference (ICI) inthe system Therefore, universal frequency-reuse transmission would be employed at cellswith sufficiently large inter-cell distances (ICD) To facilitate frequency-reuse transmis-sions for neighboring cells (having short ICD), appropriate precoding techniques can bedeployed at base stations (BS) to eliminate ICI [84], [70], [2], [95]

transmis-1.6 Motivation

The content of the thesis will focus on the following issues:

- SIR analysis for OFDM transmission in the presence of CFO, phase noise anddoubly selective fading

- Doubly selective channel estimation in full-duplex MIMO-OFDM transmission

- Precoding design and power allocation in two-way relay networks

- Inter-cell interference management in multiuser transmissions

1.7 Conclution

chan-2.2 Wireless chanel model and multi-dimension signal processing techniques2.2.1 Wireless chanel model

2.2.2 Orthogonal frequency-division multiplexing (OFDM)

yn = ej2πεnN ejφn

L−1X

l=0

N −1X

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-(PDP) of the considered channel L is the number of resolvable paths, E[ejφne−jφ0n] =

e−πβTs |n−n 0 |/N and (N − |r|) are both even functions, and J0(2πfdrTs/N ) is a normalizedPDP

r=1

(N − r)J0



2πfdrTsN



e−πβTsrN



.(2.4)

As a result, we can obtain the SIR expression:

SIR(fdTs, ε, βTs) =



N + 2

N −1Pr=1

(N − r)J0(2πrfd T s

N ) cos(2πrεN )e−πrβTsN



N −1P

∆=1



N + 2

N −1Pr=1

Figure 2.1: SIR contour versus:

To verify the validity of SIR analysis, numerical results of (2.5) versus PHN level

βTs are shown in Fig 2.3 SIR curves are provided under different CFO values It isobserved that the SIR decreases as synchronization impairments increases In addition,Fig 2.3 shows a good agreement between simulated and theoretical results (2.5)

To illustrate the need of considering the joint effect of CFO, PHN and Doppler

Figure 2.3: SIR versus PHN level βTs

under fdTs = 0.03 (v = 100 km/h)

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 15

20 25 30 35 40

Figure 2.4: SIR versus the NDF when

ε = 0.05 and βTs = 0.005

spread in SIR analysis, Fig 2.4 shows numerical results of the SIR expression (2.5) andother ones in the literature In the considered system settings, one can find that ignoringonly phase noise incurs the smallest gap between the theoretical and simulated SIR values.2.4 Doubly selective channel estimation in full-duplex MIMO-OFDM trans-mission

l=0

˙h(r,t) l,n,m˙x(t)n−l,m

Using BEMs, the channel impulse responses of desired and self-interference linkscan be approximately represented by

h(r,t)l,n,m =

QX

q=1

bn+Ng+mNs,q c(r,t)q,l , l ∈ {0, , L − 1}, (2.7)

˙h(r,t) l,n,m =

˙ QX

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-the qth basis function values of -the used BEM c(r,t)q,l and ˙c(r,t)q,l are the BEM coefficients

used for the desired and self-interference channels, respectively Q and ˙Q are the numbers

of basis functions used for the desired and self-interference channels, respectively

The lth time-variant channel tap gains of desired and self-interference channels

corresponding to the pilot OFDM symbol at the position mp in a burst can be expressed

in a vector form as follows

h(r,t)l,m

p = Bmpc(r,t)l , ˙h(r,t)l,m

p = ˙Bmp˙c(r,t)l , (2.9)where hl,mp and ˙hl,mp denote vectors of channel responses of desired and self-interference

channels, respectively

For a group of P pilot OFDM symbols, a vector representation of all related

time-variant channel tap gains can be expressed by

h(r,t) = BLc(r,t), ˙h(r,t) = ˙BL˙c(r,t), (2.10)where h(r,u) =

 h

h(r,u)l,m1

l=0

QX

l=0

˙ QX

For the formulation of the Maximum Likelihood (ML) estimation approach, the

received samples corresponding to P pilot OFDM symbols can be represented in a vector

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-2.4.2 ML-Based Channel Estimation

In particular, the ML-based estimates of BEM coefficients can be determined asfollows:

h(r,t)l,m1

iT

, ,

h b

h(r,t)l,mp

iT

, ,

h b

h(r,t)l,mP

(r,t) l,m 1

T

, ,



b˙h

(r,t) l,m p

T

, ,

2.4.3 Cram´er Rao Lower Bound Derivation

The Cram´er Rao Lower Bound of the estimated parameter ω can be obtained by

Figure 2.6: MSE of estimated BEM cients versus mobile speed (km/h)

coeffi-Fig 2.5 shows the MSE results of ML-based time-variant CIR estimates versusSNR As observed, the DPS-BEM offer the best MSE performance as compared to GCE-BEM and CE-BEM In addition, curve a illustrates a very poor MSE performance of usingblock-fading assumption under the condition of time-varying channels

Fig 2.6 shows the MSE performance of CIR estimation under the use of variousBEMs As can be seen, the performance degradation under the use of the block-fading

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-assumption becomes worse as moving node speeds increase Over time-variant channels,the problem of outdated CIR estimates incurs the poor estimation performance when usingblock-fading assumption This figure also shows that the DPS basis function can providestable MSE performance with high robustness against fast-fading channels

2.5 Conclusion

In this chapter, the author has formulated a SIR expression for OFDM transmissions

in the presence of phase noise, carrier frequency offset, and time-selective channels Theanalytical results using (2.5) showed an exact agreement with the simulation results overwide ranges of mobile speeds, CFO, and PHN

In addition, the author has formulated a BEM-based channel estimation algorithmfor full-duplex MIM-OFDM systems over doubly selective channels The proposed BEM-based full-duplex doubly selective channel estimation algorithm offered a stable perfor-mance with high robustness against fast time-variation of fading channels

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multi-hop mobile communication

3.2.5 Multi-user MIMO system model

3.2.6 Block diagonal (BD) precoding for multi-user downlink wireless

Nk In this paper,wireless channels are assumed to be block-fading and frequency-flat It is assumed thatthere is no direct link between the BS and MSs

3.3.2 Independent two phase design

Multiple Access Phase

The received signal at the relay can be expressed by

where, H = [H0, H1, , HK] matrix of channel response, P = diag{P0, P1, , PK}

is precoding matrix at BS and K MSs, s = [sT0, sT1, , sTK]T information bearing symbolsfrom BS and K MSs, s0 =