IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (ACCEPTED) 1 An Energy-Efficient Uncoordinated Cooperative Scheme with Uncertain Relay Distribution Intensity

Abstract-Due to signal fading and user mobility in wireless networks, quality-of-service (QoS) provisioning for wireless services becomes more challenging. As a promising technique, cooperative communications make use of the broadcasting nature of wireless medium to facilitate data transmission, and thereby reduce energy consumption. However, in many studies on wireless cooperative diversity, it is often assumed that the number of relays or the relay distribution intensity is known a priori. In this paper, we relax such assumption and propose an algorithm to estimate the relay intensity for a backoff-based cooperative scheme, where the relays are distributed as a homogeneous Poisson point process (PPP). It is proved that the algorithm can converge to an optimal solution with the minimum estimation error. Based on the estimated relay intensity, we further investigate a distributed energy saving strategy, which selectively turns off some relays to reduce energy consumption while maintaining the required transmission success probability. The performance of the proposed cooperative scheme is analytically evaluated with respect to the collision probability. The numerical and simulation results demonstrate the high accuracy and efficiency of the intensity estimation algorithm and also validate the theoretical analysis. Moreover, the proposed cooperative scheme exhibits significant energy saving and satisfactory transmission performance, which offers a good match to accommodate green communications in wireless networks. Index Terms-Cooperative wireless networks, distributed relaying, intensity estimation, energy efficiency

QoS in Distributed Broadband Wireless Communication (BWC) Systems with Optimum Antenna Layout

This thesis is concerned with optimization of distributed broadband wireless communication (BWC) systems. Distributed BWC systems contain a distributed antenna system (DAS) connected to a base station with optical fiber. Distributed BWC systems have been proposed as a solution to the transmit power problem in traditional cellular networks. So far, the research on BWC systems have advanced on two separate tracks, design of the system to meet the quality of service requirements (QoS) and optimization of layout of the DAS. This thesis considers a combined optimization of BWC systems. We consider uplink communications with multiple levels of priority traffic having any renewal arrival and departure processes. We develop an analysis that determines packet delay violation probability for each priority level as a function of the outage probability of the distributed antenna system. Then, we determine the optimal locations of the antennas that minimize the antenna outage probability, taking path-loss model, Rayleigh model and inter-cell interferences into account. We also study the tradeoff between the packet delay violation probability and packet loss probability

Optimizing resource allocation in eh-enabled internet of things

Internet of Things (IoT) aims to bridge everyday physical objects via the Internet. Traditional energy-constrained wireless devices are powered by fixed energy sources like batteries, but they may require frequent battery replacements or recharging. Wireless Energy Harvesting (EH), as a promising solution, can potentially eliminate the need of recharging or replacing the batteries. Unlike other types of green energy sources, wireless EH does not depend on nature and is thus a reliable source of energy for charging devices. Meanwhile, the rapid growth of IoT devices and wireless applications is likely to demand for more operating frequency bands. Although the frequency spectrum is currently scarce, owing to inefficient conventional regulatory policies, a considerable amount of the radio spectrum is greatly underutilized. Cognitive radio (CR) can be exploited to mitigate the spectrum scarcity problem of IoT applications by leveraging the spectrum holes. Therefore, transforming the IoT network into a cognitive based IoT network is essential to utilizing the available spectrum opportunistically. To address the two aforementioned issues, a novel model is proposed to leverage wireless EH and CR for IoT. In particular, the sum rate of users is maximized for a CR-based IoT network enabled with wireless EH. Users operate in a time switching fashion, and each time slot is partitioned into three non-overlapping parts devoted for EH, spectrum sensing and data transmission. There is a trade-off among the lengths of these three operations and thus the time slot structure is to be optimized. The general problem of joint resource allocation and EH optimization is formulated as a mixed integer nonlinear programming task which is NP-hard and intractable. Therefore, a sub-channel allocation scheme is first proposed to approximately satisfy users rate requirements and remove the integer constraints. In the second step, the general optimization problem is reduced to a convex optimization task. Another optimization framework is also designed to capture a fundamental tradeoff between energy efficiency (EE) and spectral efficiency for an EH-enabled IoT network. In particular, an EE maximization problem is formulated by taking into consideration of user buffer occupancy, data rate fairness, energy causality constraints and interference constraints. Then, a low complexity heuristic algorithm is proposed to solve the resource allocation and EE optimization problem. The proposed algorithm is shown to be capable of achieving a near optimal solution with polynomial complexity. To support Machine Type Communications (MTC) in next generation mobile networks, NarrowBand-IoT (NB-IoT) has emerged as a promising solution to provide extended coverage and low energy consumption for low cost MTC devices. However, the existing orthogonal multiple access scheme in NB-IoT cannot provide connectivity for a massive number of MTC devices. In parallel with the development of NB-IoT, Non-Orthogonal Multiple Access (NOMA), introduced for the fifth generation wireless networks, is deemed to significantly improve the network capacity by providing massive connectivity through sharing the same spectral resources. To leverage NOMA in the context of NB-IoT, a power domain NOMA scheme is proposed with user clustering for an NB-IoT system. In particular, the MTC devices are assigned to different ranks within the NOMA clusters where they transmit over the same frequency resources. Then, an optimization problem is formulated to maximize the total throughput of the network by optimizing the resource allocation of MTC devices and NOMA clustering while satisfying the transmission power and quality of service requirements. Furthermore, an efficient heuristic algorithm is designed to solve the proposed optimization problem by jointly optimizing NOMA clustering and resource allocation of MTC devices