Energy-Efficient and Low Signaling Overhead Cooperative Relaying With Proactive Relay Subset Selection

Energy efficient wireless communications have recently received much attention, due to the ever-increasing energy consumption of wireless communication systems. In this paper, we propose a new energy-efficient cooperative relaying scheme that selects a subset of relays before data transmission, through proactive participation of available relays using their local timers. We perform theoretical analysis of energy efficiency under maximum transmission power constraint, using practical data packet length, and taking account of the overhead for obtaining channel state information, relay selection, and cooperative beamforming. We provide the expression of average energy efficiency for the proposed scheme, and identify the optimal number and location of relays that maximise energy efficiency of the system. A closedform approximate expression for the optimal position of relays is derived. We also perform overhead analysis for the proposed scheme and study the impact of data packet lengths on energy efficiency. The analytical and simulation results reveal that the proposed scheme exhibits significantly higher energy efficiency as compared to direct transmission, best relay selection, all relay selection, and a state-of-the-art existing cooperative relaying scheme. Moreover, the proposed scheme reduces the signalling overhead and achieves higher energy savings for larger data packets

Energy-Efficient and Overhead-Aware Cooperative Communications

Due to the rapid growth of energy-hungry wireless multimedia services, telecom energy consumption is increasing at an extraordinary rate. Besides negative environmental impacts and higher energy bills for operators, it also affects user experience as improvements in battery technologies have not kept up with increasing mobile energy demands. Therefore, how to increase the energy efficiency (EE) of wireless communications has gained a lot of attention recently. Cooperative communication, where relays cooperatively retransmit the received data from the source to the destination, is seen as a promising technique to increases EE. Nevertheless, it requires more overhead than direct communication that needs to be taken into account for practical wireless cooperative networks. In order to achieve potential energy savings promised by cooperative communications in practical systems, overhead-aware cooperative relaying schemes with low overhead are imperative. For the case that not all relays can hear each other, i.e., hidden relays exist, an energy-efficient and a low-overhead cooperative relaying scheme is proposed. This scheme selects a subset of relays before data transmission, through the proactive participation of available relays using their local timers. Theoretical analysis of average EE under maximum transmission power constraint, using practical data packet length, and taking account of the overhead for obtaining channel state information (CSI), relay selection, and cooperative beamforming, is performed and a closed-form approximate expression for the optimal position of relays is derived. Furthermore, the overhead of the proposed scheme and the impact of data packet lengths on EE, are analysed. The analytical and simulation results reveal that the proposed scheme is significantly more energy-efficient than direct transmission, best relay selection, all relay selection, and a state-of-the-art existing cooperative relaying scheme. Moreover, the proposed scheme reduces the overhead and achieves higher energy savings for larger data packets. The conventional cooperative beamforming schemes rely on the feedback of CSIs of the best relays from the destination, which cause extra energy consumption and are prone to quantization errors in practical systems. In the case of clustered relays with location awareness and timer-based relay selection, where relays can overhear the transmission and know the location of each other, an energy-efficient overhead-aware cooperative relaying scheme is proposed, making CSI feedback from the destination dispensable. In order to avoid possible collisions between relay transmissions during best relays selection, a distributed mechanism for the selected relays to appropriately insert guard intervals before their transmissions is proposed. Average EE of the proposed scheme considering the related overhead is analysed. Moreover, the impact of the number of available relays, the number of selected relays and the location of relay cluster on EE is studied. The simulation results indicate that the proposed cooperative relaying scheme achieves higher EE than direct communication, best relay selection, and all relay selection for relay clusters located close to the source. Independent of the relay cluster location, the proposed scheme exhibits significantly higher EE than an existing cooperative relaying scheme. Device-to-device (D2D) communication in cellular networks that enable direct transmissions between user equipments (UEs) is seen as a promising way to improve both EE and spectral efficiency (SE). If the source UE (SUE) and the destination UE (DUE) are far away from each other or if the channel between them is too weak for direct transmission, then two-hop D2D communications, where relay UEs (RUEs) forward the SUE's data packets to the DUE, can be used. An energy- and spectral-efficient optimal adaptive forwarding strategy (OAFS) for two-hop D2D communications is proposed. In a distributed manner, the OAFS adaptively chooses between the best relay forwarding (BRF) and the cooperative relay beamforming (CRB) with the optimal number of selected RUEs, depending on which of them provides the higher instantaneous EE. In order to reduce the computational complexity of relay selection, a low-complexity sub-optimal adaptive forwarding strategy (SAFS) is proposed that selects between the BRF and the CRB with two RUEs by comparing their instantaneous EE. Theoretical analysis of the average EE and SE for the proposed adaptive forwarding strategies is performed considering maximum transmission power constraints, circuit power consumption and the overhead for the acquisition of CSI, forwarding mode selection and cooperative beamforming. The theoretical and simulation results show that the proposed OAFS and SAFS exhibit significantly higher EE and SE than the BRF, CRB, direct D2D communications and conventional cellular communications. For short to moderate SUE-to-DUE distances, SAFS is almost as energy- and spectral-efficient as OAFS

Adaptive Relay-Selection In Decode-And-Forward Cooperative Systems

In the past few years adaptive decode-and-forward cooperative diversity systems have been studied intensively in literature. Many schemes and protocols have been proposed to enhance the performance of the cooperative systems while trying to alleviate its drawbacks. One of the recent schemes that had been shown to give high improvements in performance is the best-relay selection scheme. In the best-relay selection scheme only one relaying nodes among the relays available in the system is selected to forward the source\u27s message to the destination. The best relay is selected as the relay node that can achieve the highest end-to-end signal-to-noise ratio (snr) at the destination node. Performance improvements have been reported as compared to regular fixed decode-and-forward relaying in which all relays are required to forward the source\u27s message to the destination in terms of spectral efficiency and diversity order. In this thesis, we use simulations to show the improvement in the outage performance of the best-relay selection scheme

Allocation of Communication and Computation Resources in Mobile Networks

Konvergence komunikačních a výpočetních technologií vedlo k vzniku Multi-Access Edge Computing (MEC). MEC poskytuje výpočetní výkon na tzv. hraně mobilních sítí (základnové stanice, jádro mobilní sítě), který lze využít pro optimalizaci mobilních sítí v reálném čase. Optimalizacev reálném čase je umožněna díky nízkému komunikačnímu zpoždění například v porovnání s Mobile Cloud Computing (MCC). Optimalizace mobilních sítí vyžaduje informace o mobilní síti od uživatelských zařízeních, avšak sběr těchto informací využívá komunikační prostředky, které jsou využívány i pro přenos uživatelských dat. Zvyšující se počet uživatelských zařízení, senzorů a taktéž komunikace vozidel tvoří překážku pro sběr informací o mobilních sítích z důvodu omezeného množství komunikačních prostředků. Tudíž je nutné navrhnout řešení, která umožní sběr těchto informací pro potřeby optimalizace mobilních sítí. V této práci je navrženo řešení pro komunikaci vysokého počtu zařízeních, které je postaveno na využití přímé komunikace mezi zařízeními. Pro motivování uživatelů, pro využití přeposílání dat pomocí přímé komunikace mezi uživateli je navrženo přidělování komunikačních prostředků jenž vede na přirozenou spolupráci uživatelů. Dále je provedena analýza spotřeby energie při využití přeposílání dat pomocí přímé komunikace mezi uživateli pro ukázání jejích výhod z pohledu spotřeby energie. Pro další zvýšení počtu komunikujících zařízení je využito mobilních létajících základových stanic (FlyBS). Pro nasazení FlyBS je navržen algoritmus, který hledá pozici FlyBS a asociaci uživatel k FlyBS pro zvýšení spokojenosti uživatelů s poskytovanými datovými propustnostmi. MEC lze využít nejen pro optimalizaci mobilních sítí z pohledu mobilních operátorů, ale taktéž uživateli mobilních sítí. Tito uživatelé mohou využít MEC pro přenost výpočetně náročných úloh z jejich mobilních zařízeních do MEC. Z důvodu mobility uživatel je nutné nalézt vhodně přidělení komunikačních a výpočetních prostředků pro uspokojení uživatelských požadavků. Tudíž je navržen algorithmus pro výběr komunikační cesty mezi uživatelem a MEC, jenž je posléze rozšířen o přidělování výpočetných prostředků společně s komunikačními prostředky. Navržené řešení vede k snížení komunikačního zpoždění o desítky procent.The convergence of communication and computing in the mobile networks has led to an introduction of the Multi-Access Edge Computing (MEC). The MEC combines communication and computing resources at the edge of the mobile network and provides an option to optimize the mobile network in real-time. This is possible due to close proximity of the computation resources in terms of communication delay, in comparison to the Mobile Cloud Computing (MCC). The optimization of the mobile networks requires information about the mobile network and User Equipment (UE). Such information, however, consumes a significant amount of communication resources. The finite communication resources along with the ever increasing number of the UEs and other devices, such as sensors, vehicles pose an obstacle for collecting the required information. Therefore, it is necessary to provide solutions to enable the collection of the required mobile network information from the UEs for the purposes of the mobile network optimization. In this thesis, a solution to enable communication of a large number of devices, exploiting Device-to-Device (D2D) communication for data relaying, is proposed. To motivate the UEs to relay data of other UEs, we propose a resource allocation algorithm that leads to a natural cooperation of the UEs. To show, that the relaying is not only beneficial from the perspective of an increased number of UEs, we provide an analysis of the energy consumed by the D2D communication. To further increase the number of the UEs we exploit a recent concept of the flying base stations (FlyBSs), and we develop a joint algorithm for a positioning of the FlyBS and an association of the UEs to increase the UEs satisfaction with the provided data rates. The MEC can be exploited not only for processing of the collected data to optimize the mobile networks, but also by the mobile users. The mobile users can exploit the MEC for the computation offloading, i.e., transferring the computation from their UEs to the MEC. However, due to the inherent mobility of the UEs, it is necessary to determine communication and computation resource allocation in order to satisfy the UEs requirements. Therefore, we first propose a solution for a selection of the communication path between the UEs and the MEC (communication resource allocation). Then, we also design an algorithm for joint communication and computation resource allocation. The proposed solution then lead to a reduction in the computation offloading delay by tens of percent

무선 중계 네트워크에서 신호대잡음비의 누적분포함수 기반 중계기 선택 기법의 성능 분석

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 이재홍.무선 중계 기술은 차세대 무선통신 시스템에서 요구되는 높은 서비스 품질 및 데이터 전송률 달성을 위해 고려되고 있는 대표적인 기술 중 하나이다. 무선 중계 기술이 갖고 있는 다양한 장점으로 인해 현재까지 IEEE 802.16j 및 3GPP LTE-Advanced 등의 무선통신 시스템 표준에 반영되기도 하였다. 실질적으로 두 노드 사이 채널의 통계적 특성은 그들의 위치에 따라 달라지기 때문에 각 채널들의 통계적 특성은 서로 동일하지 않다. 각 채널들의 통계적 특성이 동일하지 않을 때, 무선 중계 기술에서 가장 유용한 기법 중 하나인 중계기 선택 기법은 특정 중계기들이 더 자주 선택되는 등의 공정성 문제를 유발시킬 수 있다. 특히, 이 문제는 제한된 배터리를 가진 중계기들로 구성된 네트워크에서 네트워크의 수명을 줄이게 하는 요인이 될 수 있다. 따라서 이러한 네트워크에서는 사용자들의 통신 신뢰도 뿐만 아니라, 중계기에서의 선택 공정성도 함께 고려할 필요가 있다. 본 논문에서는 무선 중계 네트워크에서 사용자들의 통신 신뢰도와 중계기 간의 선택 공정성을 함께 고려하기 위해 수신 신호대잡음비의 누적분포함수를 기반으로 하는 새로운 중계기 선택 기법을 제안한다. 주요한 연구 결과는 다음과 같다. 먼저, 나카가미-m 페이딩 채널 환경을 가진 일방향 중계 네트워크를 위한 프로액티브(proactive) 및 리액티브(reactive) 방식의 수신 신호대잡음비 누적분포함수 기반 중계기 선택 기법을 제안한다. 각각의 중계기 선택 기법을 위해 중계기 선택 확률을 유도하여 제안된 각 중계기 선택 기법들의 평균 중계기 공정성을 분석한다. 또한 각 선택 기법에 대한 불능 확률을 수식으로 유도하고, 유도한 불능 확률을 점근적 표현으로 나타내어 각 기법들이 얻을 수 있는 다이버시티 차수를 분석한다. 모의실험을 통해 얻어진 평균 중계기 공정성과 불능 확률이 유도한 평균 중계기 공정성 및 불능 확률 값과 일치함을 확인한다. 그리고 제안된 기법이 중계기들 사이에 공정성을 완벽하게 보장하고 네트워크 수명을 증가시키며, 다이버시티 차수가 중계기의 수와 페이딩 파라미터 m 값에 따라 달라짐을 확인한다. 둘째, 나카가미-m 페이딩 채널 환경을 가진 양방향 중계 네트워크를 위한 프로액티브 및 리액티브 방식의 수신 신호대잡음비 누적분포함수 기반 중계기 선택 기법을 제안한다. 제안된 프로액티브 방식의 중계기 선택 기법에 대해서는 정확한 중계기 선택 확률의 유도를 통해 평균 중계기 공정성을 분석한다. 제안된 리액티브 방식의 중계기 선택 기법에 대해서는 중계기 선택 확률의 적분 및 근사 표현을 유도하여 평균 중계기 공정성을 분석한다. 또한 각 선택 기법에 대한 불능 확률을 수식으로 유도하고, 유도한 불능 확률을 점근적 표현으로 나타내어 각 기법들이 얻을 수 있는 다이버시티 차수를 분석한다. 모의실험을 통해 얻어진 평균 중계기 공정성과 불능 확률이 유도한 평균 중계기 공정성 및 불능 확률 값과 일치함을 확인한다. 그리고 제안된 기법이 중계기들 사이에 공정성을 완벽하게 보장하고 네트워크 수명을 증가시키며, 다이버시티 차수가 중계기의 수와 페이딩 파라미터 m 값에 따라 달라짐을 확인한다.Wireless relay technology is one of the most promising technologies for the future communication systems which provide coverage extension and better quality of service (QoS) such as higher data rate and lower outage probability with few excessive network loads. Due to its advantages, it has been adopted in wireless standards such as IEEE 802.16j and 3GPP LTE-Advanced. In practice, since statistics of the channel between any two nodes vary depending on their locations, they are not identical which means that channels can experience different fading. When statistics of the channel are not identical, relay selection, which is one of the most useful techniques for wireless relay technology, can cause fairness problem that particular relays are selected more frequently than other relays. Especially, this problem can cause reduction of lifetime in the network with multiple relays having limited battery power. In this network, it is needed to focus on selection fairness for relays as well as reliability at end-users. In this dissertation, to focus on both selection fairness for relays and reliability at end-users, we propose novel relay selection schemes based on cumulative distribution functions (CDFs) of signal-to-noise ratios (SNRs) in wireless relay networks. The dissertation consists of two main results. First, we propose the proactive and the reactive relay selection schemes based on CDFs of SNRs for one-way relay networks over Nakagami-m fading channels. If a relay is selected before the source transmission, it is called as proactive relay selection. Otherwise, if a relay is selected after the source transmission, it is called as reactive relay selection. For both the proactive and the reactive relay selection schemes, we analyze average relay fairness by deriving relay selection probability. For the proactive relay selection scheme, we obtain diversity order by deriving the integral and asymptotic expressions for outage probability. Also, for the reactive relay selection scheme, we obtain diversity order by deriving the exact closed-form and asymptotic expressions for outage probability. Numerical results show that the analytical results of the proposed schemes match the simulation results well. It is shown that the proposed schemes guarantee strict fairness among relays and extend network lifetime. Also, it is shown that diversity order depends on the number of relays and fading severity parameters. Second, we propose the proactive and the reactive relay selection schemes based on CDFs of SNRs for two-way relay networks over Nakagami-m fading channels. For the proactive relay selection scheme, we analyze average relay fairness by deriving relay selection probability. Also, we analyze diversity order by deriving the integral and asymptotic expressions for outage probability. For the reactive relay selection scheme, we analyze average relay fairness by deriving the integral and asymptotic expressions for relay selection probability. Also, we obtain diversity order by deriving the asymptotic expression for outage probability. Numerical results show that the analytical results of the proposed schemes match the simulation results well. It is shown that the proposed schemes guarantee strict fairness among relays and extend network lifetime. Also, it is shown that diversity order depends on the number of relays and fading severity parameters.Contents Abstract i 1 Introduction 1 1.1 Background and Related Work . . . . . . . . . . . . . . . . . . . . . 2 1.1.1 Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.2 Wireless Relay Technology . . . . . . . . . . . . . . . . . . . . 3 1.2 Outline of Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.3 Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2 Relay Selection Based on CDFs of SNRs for One-Way Relay Networks 14 2.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.1.1 Proactive CDF-Based Relay Selection . . . . . . . . . . . . . 19 2.1.2 Reactive CDF-Based Relay Selection . . . . . . . . . . . . . . 20 2.2 Performance Analysis of Proactive CDF-Based Relay Selection . . . . 22 2.2.1 Average Relay Fairness Analysis . . . . . . . . . . . . . . . . . 22 2.2.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 27 2.3 Performance Analysis of Reactive CDF-Based Relay Selection . . . . 34 2.3.1 Average Relay Fairness Analysis . . . . . . . . . . . . . . . . . 34 2.3.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 36 2.4 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.4.1 Average Relay Fairness . . . . . . . . . . . . . . . . . . . . . . 39 2.4.2 Network Lifetime . . . . . . . . . . . . . . . . . . . . . . . . . 48 2.4.3 Outage Probability . . . . . . . . . . . . . . . . . . . . . . . . 53 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3 Relay Selection Based on CDFs of SNRs for Two-Way Relay Networks 66 3.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.1.1 Proactive CDF-based Relay Selection . . . . . . . . . . . . . . 68 3.1.2 Reactive CDF-based Relay Selection . . . . . . . . . . . . . . 72 3.2 Performance Analysis of Proactive CDF-Based Relay Selection . . . . 73 3.2.1 Average Relay Fairness Analysis . . . . . . . . . . . . . . . . . 73 3.2.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 74 3.3 Performance Analysis of Reactive CDF-Based Relay Selection . . . . 82 3.3.1 Average Relay Fairness Anlaysis . . . . . . . . . . . . . . . . . 82 3.3.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 86 3.4 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 3.4.1 Average Relay Fairness . . . . . . . . . . . . . . . . . . . . . . 89 3.4.2 Network Lifetime . . . . . . . . . . . . . . . . . . . . . . . . . 100 3.4.3 Outage Probability . . . . . . . . . . . . . . . . . . . . . . . . 105 3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 4 Conclusion 116 4.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 4.2 Possible Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 4.2.1 Device-to-Device (D2D) Communications . . . . . . . . . . . 118 4.2.2 Low Power Body Sensor Networks . . . . . . . . . . . . . . . 120 4.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Bibliography 122 Korean Abstract 139Docto

A Study Of Cooperative Spectrum Sharing Schemes For Internet Of Things Systems

The Internet of Things (IoT) has gained much attention in recent years with the massive increase in the number of connected devices. Cognitive Machine-to-Machine (CM2M) communications is a hot research topic in which a cognitive dimension allows M2M networks to overcome the challenges of spectrum scarcity, interference, and green requirements. In this paper, we propose a Generalized Cooperative Spectrum Sharing (GCSS) scheme for M2M communication. Cooperation extends the coverage of wireless networks as well as increasing their throughput while reducing the energy consumption of the connected low power devices. We study the outage performance of the proposed GCSS scheme for M2M system and derive exact expressions for the outage probability. We also analyze the effect of varying transmission powers on the performance of the system