Improvement in Performance of Wireless Relay Nodes Using Physical Layer Network Coding

Recent advancements in high data rate networks have led to a growing interest in improving performance of wireless relay networks through the use of Physical Layer Network Coding (PLNC) technique. In the PLNC technique, the relay node exploits the network coding operation that occurs naturally when the two electromagnetic (EM) waves are superimposed on one another to directly decode the modulo-2 sum of the transmitted symbols. In this thesis, we will present an optimal power control algorithm for performance improvement in wireless relay nodes implementing physical layer network coding. We shall also present a sub-optimal power control algorithm and compare its performance with the optimal power control algorithm. Our approach will first derive the probability of error for the amplitude-controlled system using Maximum Likelihood detection and then minimize the probability of error using amplitude control functions as variables to derive the optimal power control functions. We shall start by considering the thresholds of the system to be the maximum of the independent received amplitudes to derive the probability of error equations and then extend it to a variable threshold system, where the threshold is a function of independent received amplitudes. We then derive an optimal power control algorithm for a single channel Rayleigh system and implement this power control algorithm independently on the terminals to achieve a sub-optimal power control algorithm. Our results show that the proposed optimal power control algorithm boosts the performance of the PLNC system significantly compared to the no power control system. We also show that there are no significant differences between the performances of optimal power control and the sub-optimal power control algorithms. We further show that the performance of the system is not degraded much when the amplitudes of the terminals deviate from the optimal amplitudes

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

A White Paper on Broadband Connectivity in 6G

Executive Summary This white paper explores the road to implementing broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, from extreme capacity with peak data rates up to 1 Tbps, to raising the typical data rates by orders-of-magnitude, to support broadband connectivity at railway speeds up to 1000 km/h. To achieve these goals, not only the terrestrial networks will be evolved but they will also be integrated with satellite networks, all facilitating autonomous systems and various interconnected structures. We believe that several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric and scalable cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be used for pushing the peak rates of point-to-point links. The latter path will lead to THz communications complemented by visible light communications in specific scenarios. At the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latencies, higher reliability, and reduced complexity. Different options will be needed to optimally support different use cases. The resource efficiency can be further improved by using various combinations of full-duplex radios, interference management based on rate-splitting, machine-learning-based optimization, coded caching, and broadcasting. Finally, the three levels of enablers must be utilized not only to deliver better broadband services in urban areas, but also to provide full-coverage broadband connectivity must be one of the key outcomes of 6G