Synchronization in Cooperative Communication Systems

Cooperative communication is an attractive solution to combat fading in wireless communication systems. Achieving synchronization is a fundamental requirement in such systems. In cooperative networks, multiple single antenna relay terminals receive and cooperatively transmit the source information to the destination. The multiple distributed nodes, each with its own local oscillator, give rise to multiple timing offsets (MTOs) and multiple carrier frequency offsets (MCFOs). Particularly, the received signal at the destination is the superposition of the relays' transmitted signals that are attenuated differently, are no longer aligned with each other in time, and experience phase rotations at different rates due to different channels, MTOs, and MCFOs, respectively. The loss of synchronization due to the presence of MTOs and MCFOs sets up the recovery of the source signal at the destination to be a very challenging task. This thesis seeks to develop estimation and compensation algorithms that can achieve synchronization and enable cooperative communication for both decode-and-forward (DF) and amplify-and-forward (AF) relaying networks in the presence of multiple impairments, i.e., unknown channel gains, MTOs, and MCFOs. In the first part of the thesis, a training-based transmission scheme is considered, in which training symbols are transmitted first in order to assist the joint estimation of multiple impairments at the destination node in DF and AF cooperative relaying networks. New transceiver structure at the relays and novel receiver design at the destination are proposed which allow for the decoding of the received signal in the presence of unknown channel gains, MTOs, and MCFOs. Different estimation algorithms, e.g., least squares (LS), expectation conditional maximization (ECM), space-alternating generalized expectation-maximization (SAGE), and differential evolution (DE), are proposed and analyzed for joint estimation of multiple impairments. In order to compare the estimation accuracy of the proposed estimators, Cramer-Rao lower bounds (CRLBs) for the multi-parameter estimation are derived. Next, in order to detect the signal from multiple relays in the presence of multiple impairments, novel optimal and sub-optimal minimum mean-square error (MMSE) compensation and maximum likelihood (ML) decoding algorithm are proposed for the destination receiver. It has been evidenced by numerical simulations that application of the proposed estimation and compensation methods in conjunction with space-time block codes achieve full diversity gain in the presence of channel and synchronization impairments. Considering training-based transmission scheme, this thesis also addresses the design of optimal training sequences for efficient and joint estimation of MTOs and multiple channel parameters. In the second part of the thesis, the problem of joint estimation and compensation of multiple impairments in non-data-aided (NDA) DF cooperative systems is addressed. The use of blind source separation is proposed at the destination to convert the difficult problem of jointly estimating the multiple synchronization parameters in the relaying phase into more tractable sub-problems of estimating many individual timing offsets and carrier frequency offsets for the independent relays. Next, a criteria for best relay selection is proposed at the destination. Applying the relay selection algorithm, simulation results demonstrate promising bit-error rate (BER) performance and realise the achievable maximum diversity order at the destination

Multi-Relay Communications in the Presence of Phase Noise and Carrier Frequency Offsets

Impairments like time varying phase noise (PHN) and carrier frequency offset (CFO) result in loss of synchronization and poor performance of multi-relay communication systems. Joint estimation of these impairments is necessary in order to correctly decode the received signal at the destination. In this paper, we address spectrally-efficient multi-relay transmission scenarios where all the relays simultaneously communicate with the destination. We propose an iterative pilot-aided algorithm based on the expectation conditional maximization (ECM) for joint estimation of multipath channels, Wiener PHNs, and CFOs in decode-and-forward (DF) based multi-relay orthogonal frequency division multiplexing (OFDM) systems. Next, a new expression of the hybrid Cramér-Rao lower bound (HCRB) for the multi-parameter estimation problem is derived. Finally, an iterative receiver based on an extended Kalman filter (EKF) for joint data detection and PHN tracking is employed. Numerical results show that the proposed estimator outperforms existing algorithms and its mean square error performance is close to the derived HCRB at differnt signal-to-noise ratios (SNRs) for different PHN variances. In addition, the combined estimation algorithm and iterative receiver can significantly improve average bit-error rate (BER) performance compared to existing algorithms. In addition, the BER performance of the proposed system is close to the ideal case of perfect channel impulse responses (CIRs), PHNs and CFOs estimation

Iterative optimization for max-min SINR in dense small-cell multiuser MISO SWIPT system

Considering a dense small-cell network with simultaneous wireless information and power transfer (SWIPT), this work jointly designs transmit beamformers at the base stations (BSs) and receive power splitting ratios at the users (UEs). Our objectives is to maximize the minimum UE signalto-interference-plus-noise-ratio (SINR) under BS transmit power and UE minimum harvested energy constraints. This problem is highly nonconvex, for which semidefinite programming (SDP) relaxation may even fail to locate a feasible solution. We propose an efficient spectral optimization method by expressing the rank-one constraints as a single reverse convex nonsmooth constraint and incorporating it in the optimization objective. The proposed algorithm practically achieves the theoretical bound given by SDP relaxation with almost similar complexity.ARC Discovery Projects Grant DP14010113

Estimation of Synchronization Parameters in AF Cooperative Networks

In cooperative networks, multiple carrier frequency offsets (MCFOs) and multiple timing offsets (MTOs) originate due to multiple distributed nodes. In this paper, algorithms for joint estimation of these parameters and channels in amplify-and-forward (AF) relaying networks are proposed. A new training model and transceiver structure at the relays for achieving synchronization throughout the network is devised. New exact closed-form expressions for the Cram´er-Rao lower bounds (CRLBs) for the multi-parameter estimation problem are derived. An estimation method is proposed for jointly estimating MCFOs, MTOs, and channel gains at the destination based on space-alternating generalized expectation maximization (SAGE) and compared to a computationally-intensive least squares (LS) approach. The proposed estimator’s performance is shown to be close to the CRLB at mid-to-high signal-to-noise ratio (SNR) resulting in significant cooperative performance gains in the presence of practical impairments

Residual Self-Interference Cancellation and Data Detection in Full-Duplex Communication Systems

Residual self-interference cancellation is an important practical requirement for realizing the full potential of full-duplex (FD) communication. Traditionally, the residual selfinterference is cancelled via digital processing at the baseband, which requires accurate knowledge of channel estimates of the desired and self-interference channels. In this work, we consider point-to-point FD communication and propose a superimposed signaling technique to cancel the residual self-interference and detect the data without estimating the unknown channels. We show that when the channel estimates are not available, data detection in FD communication results in ambiguity if the modulation constellation is symmetric around the origin. We demonstrate that this ambiguity can be resolved by superimposed signalling, i.e., by shifting the modulation constellation away from the origin, to create an asymmetric modulation constellation. We compare the performance of the proposed detection method to that of the conventional channel estimation-based detection method, where the unknown channels are first estimated and then the data signal is detected. Simulations show that for the same average energy over a transmission block, the bit error rate performance of the proposed detection method is better than that of the conventional method. The proposed method does not require any channel estimates and is bandwidth efficient

Evaluation of ultra-wideband in vivo radio channel and its effects on system performance

This paper presents bit‐error‐rate (BER) performance analysis and improvement using equalizers for an in vivo radio channel at ultra‐wideband frequencies (3.1 GHz to 10.6 GHz). By conducting simulations using a bandwidth of 50 MHz, we observed that the in vivo radio channel is affected by small‐scale fading. This fading results in intersymbol interference affecting upcoming symbol transmission, causing delayed versions of the symbols to arrive at the receiver side and causes increase in BER. A 29‐taps channel was observed from the experimentally measured data using a human cadaver, and BER was calculated for the measured in vivo channel response along with the ideal additive white Gaussian noise and Rayleigh channel models. Linear and nonlinear adaptive equalizers, ie, decision feedback equalizer (DFE) and least mean square (LMS), were used to improve the BER performance of the in vivo radio channel. It is noticed that both the equalizers improve the BER but DFE has better BER compared to LMS and shows the 2‐dB and 4‐dB performance gains of DFE over the LMS at Eb/No = 12 dB and at Eb/No = 14 dB, respectively. The current findings will help guide future researchers and designers in enhancing systems performance of an ultra‐wideband in vivo wireless systems

On the Effective Capacity of IRS-assisted wireless communication

We consider futuristic, intelligent reflecting surfaces (IRS)-aided communication between a base station (BS) and a user equipment (UE) for two distinct scenarios: a single-input, single-output (SISO) system whereby the BS has a single antenna, and a multi-input, single-output (MISO) system whereby the BS has multiple antennas. For the considered IRS-assisted downlink, we compute the effective capacity (EC), which is a quantitative measure of the statistical quality-of-service (QoS) offered by a communication system experiencing random fading. For our analysis, we consider the two widely-known assumptions on channel state information (CSI) -- i.e., perfect CSI and no CSI, at the BS. Thereafter, we first derive the distribution of the signal-to-noise ratio (SNR) for both SISO and MISO scenarios, and subsequently derive closed-form expressions for the EC under perfect CSI and no CSI cases, for both SISO and MISO scenarios. Furthermore, for the SISO and MISO systems with no CSI, it turns out that the EC could be maximized further by searching for an optimal transmission rate $r^*$, which is computed by exploiting the iterative gradient-descent method. We provide extensive simulation results which investigate the impact of the various system parameters, e.g., QoS exponent, power budget, number of transmit antennas at the BS, number of reflective elements at the IRS etc., on the EC of the system

An introduction to the 1998-99 Pakistan socioeconomic survey (PSES)

This brief paper is quite focused. It describes the methodology and scope of the household survey carried out by the PIDE between March and July 1999, with an aim to generate nationally representative data to examine the incidence of poverty and distribution of income. It also includes information on household composition, schooling, labour market, sources of income, credit, fertility, child mortality, health, and nutrition. The next section outlines the objectives of the household survey, followed by the design of the survey as proposed in the MIMAP project. The modified design is presented in Section 4, followed by a discussion on the seasonality in Section 5. The contents of the questionnaire are discussed briefly in Section 6. A brief description of the experience of pre-testing the questionnaire is the subject matter of the next section. Nature of the training imparted to field enumerators is reported in Section 8. The processing of data and scope of the survey are discussed respectively in Sections 9 and 10. The sample characteristics are reported in the last section