Dispensing with Channel Estimation…

In this article, we investigate the feasibility of noncoherent detection schemes in wireless communication systems as a low-complexity alternative to the family of coherent schemes. The noncoherent schemes require no channel knowledge at the receiver for the detection of the received signal, while the coherent schemes require channel inherently complex estimation, which implies that pilot symbols have to be transmitted resulting in a wastage of the available bandwidth as well as the transmission power

Initial synchronisation of wideband and UWB direct sequence systems: single- and multiple-antenna aided solutions

This survey guides the reader through the open literature on the principle of initial synchronisation in single-antenna-assisted single- and multi-carrier Code Division Multiple Access (CDMA) as well as Direct Sequence-Ultra WideBand (DS-UWB) systems, with special emphasis on the DownLink (DL). There is a paucity of up-to-date surveys and review articles on initial synchronization solutions for MIMO-aided and cooperative systems - even though there is a plethora of papers on both MIMOs and on cooperative systems, which assume perfect synchronization. Hence this paper aims to ?ll the related gap in the literature

Indoor wireless communications and applications

Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter

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

Multiple Satellites Collaboration for Joint Code-aided CFOs and CPOs Estimation

Low Earth Orbit (LEO) satellites are being extensively researched in the development of secure Internet of Remote Things (IoRT). In scenarios with miniaturized terminals, the limited transmission power and long transmission distance often lead to low Signal-to-Noise Ratio (SNR) at the satellite receiver, which degrades communication performance. A solution to address this issue is the utilization of cooperative satellites, which can combine signals received from multiple satellites, thereby significantly improve SNR. However, in order to maximize the combination gain, the signal coherent combining is necessary, which requires the carrier frequency and phase of each receiving signal to be aligned. Under low SNR circumstances, carrier parameter estimation can be a significant challenge, especially for short burst transmission with no training sequence. In order to tackle it, we propose an iterative code-aided estimation algorithm for joint Carrier Frequency Offset (CFO) and Carrier Phase Offset (CPO). The Cram\'er-Rao Lower Bound (CRLB) is suggested as the limit on the parameter estimation performance. Simulation results demonstrate that the proposed algorithm can approach Bit Error Rate (BER) performance bound within 0.4 dB with regards to four-satellite collaboration