Distributed multi-hop reservation scheme for wireless personal area ultra-wideband networks

Ultra-wideband (UWB) technology is a promising technology for multimedia applications in wireless personal area networks (WPANs) that supports very high data rates with lower power transmission for short range communication. The limitation of coverage radius of UWB network necessitates for multihop transmissions. Unfortunately, as the number of hops increases, the quality of service (QoS) degrades rapidly in multihop network. The main goal of this research is to develop and enhance multihop transmission that ensures QoS of real time traffic through the proposed distributed multihop reservation (DMR) scheme. The DMR scheme consists of two modules; distributed multihop reservation protocol (DMRP) and path selection. DMRP incorporates resource reservation, routing and connection setup that are extended on the existing WiMedia Media Access Control protocol (MAC). On the other hand, the path selection determines the optimal path that makes up the multihop route. The path selection selects nodes based on the highest Signal to Interference and Noise Ratio (SINR). The performance of DMR scheme has been verified based on the performance of the video traffic transmission. The main metrics of QoS are measured in terms of Peak Signal- to- Noise ratio (PSNR), End-to-End (E2E) delay, and throughput. The results show that DMRP compared to Multiple Resources Reservation Scheme (MRRS) in six (6) hops transmission has enhanced the average PSNR by 16.5%, reduced the average E2E delay by 14.9% and has increased the throughput by 11.1%. The DMR scheme which is the inclusion of path selection in DMRP has been compared to Link Quality Multihop Relay (LQMR). DMR scheme has improved the video quality transmission by 17.5%, reduced the average E2E delay by 18.6% and enhanced the average throughput by 20.3%. The QoS of six (6) hops transmission employing DMR scheme is almost sustained compared to two hops transmission with the QoS experiencing only slight degradation of about 2.0%. This is a considerable achievement as it is well known that as the number of hops increases the QoS in multihop transmission degrades very rapidly. Thus DMR scheme has shown to significantly improve the performance of real time traffic on UWB multihop network. In general, DMR can be applied to any WPAN network that exploit multihop transmission

Achieving Ultra-Low Latency in 5G Millimeter Wave Cellular Networks

The IMT 2020 requirements of 20 Gbps peak data rate and 1 millisecond latency present significant engineering challenges for the design of 5G cellular systems. Use of the millimeter wave (mmWave) bands above 10 GHz --- where vast quantities of spectrum are available --- is a promising 5G candidate that may be able to rise to the occasion. However, while the mmWave bands can support massive peak data rates, delivering these data rates on end-to-end service while maintaining reliability and ultra-low latency performance will require rethinking all layers of the protocol stack. This papers surveys some of the challenges and possible solutions for delivering end-to-end, reliable, ultra-low latency services in mmWave cellular systems in terms of the Medium Access Control (MAC) layer, congestion control and core network architecture

Radio Resource Management for Wireless Mesh Networks Supporting Heterogeneous Traffic

Wireless mesh networking has emerged as a promising technology for future broadband wireless access, providing a viable and economical solution for both peer-to-peer applications and Internet access. The success of wireless mesh networks (WMNs) is highly contingent on effective radio resource management. In conventional wireless networks, system throughput is usually a common performance metric. However, next-generation broadband wireless access networks including WMNs are anticipated to support multimedia traffic (e.g., voice, video, and data traffic). With heterogeneous traffic, quality-of-service (QoS) provisioning and fairness support are also imperative. Recently, wireless mesh networking for suburban/rural residential areas has been attracting a plethora of attentions from industry and academia. With austere suburban and rural networking environments, multi-hop communications with decentralized resource allocation are preferred. In WMNs without powerful centralized control, simple yet effective resource allocation approaches are desired for the sake of system performance melioration. In this dissertation, we conduct a comprehensive research study on the topic of radio resource management for WMNs supporting multimedia traffic. In specific, this dissertation is intended to shed light on how to effectively and efficiently manage a WMN for suburban/rural residential areas, provide users with high-speed wireless access, support the QoS of multimedia applications, and improve spectrum utilization by means of novel radio resource allocation. As such, five important resource allocation problems for WMNs are addressed, and our research accomplishments are briefly outlined as follows: Firstly, we propose a novel node clustering algorithm with effective subcarrier allocation for WMNs. The proposed node clustering algorithm is QoS-aware, and the subcarrier allocation is optimality-driven and can be performed in a decentralized manner. Simulation results show that, compared to a conventional conflict-graph approach, our proposed approach effectively fosters frequency reuse, thereby improving system performance; Secondly, we propose three approaches for joint power-frequency-time resource allocation. Simulation results show that all of the proposed approaches are effective in provisioning packet-level QoS over their conventional resource allocation counterparts. Our proposed approaches are of low complexity, leading to preferred candidates for practical implementation; Thirdly, to further enhance system performance, we propose two low-complexity node cooperative resource allocation approaches for WMNs with partner selection/allocation. Simulation results show that, with beneficial node cooperation, both proposed approaches are promising in supporting QoS and elevating system throughput over their non-cooperative counterparts; Fourthly, to further utilize the temporarily available radio spectrum, we propose a simple channel sensing order for unlicensed secondary users. By sensing the channels according to the descending order of their achievable rates, we prove that a secondary user should stop at the first sensed free channel for the sake of optimality; and Lastly, we derive a unified optimization framework to effectively attain different degrees of performance tradeoff between throughput and fairness with QoS support. By introducing a bargaining floor, the optimal tradeoff curve between system throughput and fairness can be obtained by solving the proposed optimization problem iteratively

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig