Outage-optimal relay selection in wireless sensor networks using fuzzy comprehensive evaluation

We propose in this paper, a strategy to minimize the total transmit power in a decode-and-forward (DF) multi-user, multi-relay cooperative uplink, such that each user satisfies its data rate. The base station performs optimal relay selection and also allocates optimal source and relay transmit powers by using the proposed algorithm. The relay selection is based upon the instantaneous user to base station channels, inter-user channels and also the target rates of the users. The simulation results indicate significant power savings over a non-cooperative uplink, under proposed joint relay selection and power minimization algorithm in a DF cooperative uplink when using a space-time coded cooperative diversity.

This paper studies on the relaying selective matter in amplify-and-forward (AF) cooperation communication with full-duplex (FD) activity. Various relay choice models supposing the present of different instant information are investigated. We examine a maximal relaying choice that optimizes the instant FD channel capacity and asks for global channel state information (CSI) as well as partial CSI learning. To make comparison easy, accurate outage probability clauses and asymptote form of these strategies that give a diversity rank are extracted. From that, we can see clearly that the number of relays, noise factor, the transmittance coefficient as well as the information transfer power had impacted on their performance. Besides, the optimal relay selection (ORS) model can promote than that of the partial relay selection (PRS) model.

Cooperative communication in wireless relay systems can improve the physical layer security, and the relay selection has great impacts on the security performances. In this paper the relay selection in Amplify-and-Forward (AF) cooperative networks is investigated. The system model constitutes of a source, an eavesdropper, a destination, and a number of intermediate nodes with secrecy constraints. The proposed optimal selection (OS) algorithm is based on the instantaneous channel state information (CSI) of two hops, jointly protects the target destination against eavesdropping and interference. To simplify the complexity of OS, the suboptimal selection (SS) algorithm is also presented, which is based on the instantaneous of the first hop and the statistical CSI of the second hop respectively. The secrecy capacity and secrecy outage probability of these two relay selection algorithms are analyzed. Simulation results of OS and SS validate our theoretical analysis and show enhancement in the secrecy rate over the direct transmission.

In this paper, we study the secrecy performance of a wirelessly powered relay-aided system, where a pair of legal users (source-destination) communicate in the presence of multiple untrusted relays. All of the nodes mentioned above are energy constrained and powered by a dedicated power beacon (PB). To prevent the untrusted relays from intercepting the source message and to achieve positive secrecy rate, the destination-based cooperative jamming technique is employed. Besides, the optimal time allocation coefficient to maximize the secrecy throughput and the optimal transmit power of PB to maximize the secrecy energy efficiency are addressed. Specifically, three relay selection schemes with various requirements for channel state information (CSI), i.e., random relay selection, partial relay selection and optimal relay selection are also proposed to enhance the system security further. Finally, simulation results indicate the cooperative jamming technique indeed achieve positive secrecy rate and the proposed optimization strategies can improve the system performance.

In this paper, we investigate the outage performance of an amplify-and-forward (AF) multiple input multiple output (MIMO) opportunistic relay selection system under time-varying channels. A practical scenario is considered, where both the relay selection and the beamforming transmission are performed with outdated channel state information (CSI), due to channel fluctuations and delays involved in relay selection and CSI feedback. To provide efficient means of evaluating the outage performance, a closed-form expression for the outage probability is given. The effects of parameters, such as the correlation between the outdated and current CSI, the number of antennas are also analyzed. All the analytical results are validated by Monte Carlo simulations.

SummaryThis paper addresses the problems of relay selection, clustering, and routing to extend the lifetime of wireless body area networks. We first propose an efficient algorithm called “Energy‐aware Relay Selection and Cluster‐based Routing (ERSCR)” to develop a hybrid data aggregation tree in the network. ERSCR has three phases, including the relay selection, clustering and Cluster Head (CH) selection, and data transmission. It divides the biosensors into several clusters and selects an appropriate CH for each cluster. Each biosensor transmits data to its CH or relay node. The aggregated data are then routed to the sink through an energy‐balanced routing tree. The proposed scheme considers both residual energy and distance for routing data of biosensors. It not only reduces the energy consumption in the network but also balances the energy consumed by different biosensors. Subsequently, we improve the ERSCR algorithm and introduce the “Joint Relay Selection, Clustering, and Routing (JRSCR)” algorithm to achieve a better network performance. JRSCR benefits from the advantages of the ERSCR algorithm. Moreover, it reduces the number of transmissions with the direct use of the relay nodes as CH. As another advantage, both ERSCR and JRSCR algorithms are compatible with the natural physical states of the human body. Simulation results demonstrate the efficiency of the proposed algorithms in terms of energy consumption, network lifetime, and maximum hop count.

Opportunistic relay selection (RS) is an efficient method to obtain diversity gain in analogue network coding (ANC) protocol with multiple relays. However, in networks with mobile relays, the channel state information (CSI) used in the RS procedure becomes outdated because of the time-varying nature of fading channels, which severely deteriorates the system performance. In this study, the authors study the RS strategy which aims to optimise the outage performance of the ANC protocol with multiple mobile relays. RS schemes for two different cases are designed, that is, (i) the scheme with only the outdated CSI during the RS procedure, and (ii) the scheme with both the outdated CSI and the statistical knowledge of channels during the RS procedure. The closed-form expressions of the outage probabilities as well as the asymptotic expressions are analytically derived for the proposed schemes, and moreover, the achievable diversities are analysed based on the asymptotic expressions. Simulation results are presented to evaluate the performances while validate the theoretical analyses for the proposed schemes.

In this paper we analyze the performance of opportunistic decode-and-forward relay selection under cooperative spectrum sharing where the available channel state information (CSI) is imperfect due to time variations of the channel coefficients or channel estimation errors. Due to imperfect CSI the secondary user (SU) cannot satisfy its interference threshold at the primary user (PU), and in fact the probability of exceeding this threshold is higher than 0.5. Therefore we define two power margin factors for the transmission power of the secondary source and the retransmission power of the secondary relays. Power margin factors determine the level of back-off from transmitters' peak powers. We then derive the outage probability of the SU and the probability of interference to the PU. Numerical results are presented from analysis which closely match those from simulations. It is shown that with proper selection of the power margin factors, a desired value of interference probability or a desired outage probability can be achieved.

Multi-carrier relay selection is of particular interest and challenge due to the spatio-frequency coupling and the dynamics of available spectral and relay resources. Among a number of promising relay selection schemes, combined relay selection stands out as an equilibrium between system complexity and reliability. Recent research progress has witnessed the capability of neural computing as a powerful tool to efficiently realize combined relay selection for a given network topology where the number of relays and their locations are fixed and known. However, for contemporary wireless networks that are highly dynamic, the classic neural computing methods can hardly help out because of the scale drifts of input and output matrices. To enable multi-carrier combined relay selection in stochastic wireless networks (SWNs) where the number of available relays for selection could vary, we propose a recurrent neural network (RNN) based framework and devise several training methods suited for various application scenarios. In addition, we conduct a set of computer experiments to verify the effectiveness and efficiency of the proposed RNN-based framework compared with several baselines. With the obtained experimental results, we also evaluate and discuss the proposed framework's reliability, generalization ability, and the robustness against imperfect channel state information (CSI).

A relay selection algorithm is proposed to improve the system performance based on statistical channel state information(CSI) in amplify-and-forward(AF) cooperative networks. An exact and upper bound ergodic capacity formulation were derived for AF relay selection network. Theoretical analysis and simulation results validate the Tightness and feasibility of upper bound ergodic capacity.

In order to balance between optimality and operation efficiency of relay selection algorithm, an efficient relay selection algorithm has been raised based on bit error rate (BER) in an amplify-and-forward (AF) collaborated relay network. The algorithm, based on characters of channel statistical information and system BER, adds gain parameter of equivalent channel, sets SNR as threshold, select relay node assembly in the condition of same power, so as to minimize system BER. This algorithm has equal performance with Full Search Algorithm but with simpler calculation. Performance of the relay selection calculation BER is better than other algorithm by forwarding and preselecting an optimal relay node.

As a special type of mobile ad hoc networks (MANETs), vehicular ad hoc networks (VANETs) are expected to support vehicle to vehicle communication and vehicle to infrastructure communication. The conventional relay selection scheme proposed for MANETs may perform poorly in VANETs due to the unique characteristics of VANETs, including highly dynamic network topology, unstable link status and multiple types of services with various QoS requirements. In the paper, a relay vehicle selection algorithm is proposed for a VANET with multiple source vehicles (SVs) and relay vehicles (RVs). Stressing the cooperation and competitive relationship among SVs and RVs in relay selection, a cooperative Game model is formulated. To achieve the maximization of joint payoff functions of all the SVs and RVs, modified Kuhn-Munkres algorithm is applied and the optimal relay vehicle selection is obtained. Numerical results demonstrate that compared with previous scheme, the proposed scheme offers better performance in terms of throughput, successful transmission rate and transmission delay.

In this paper, we consider relay selection for turbo coded cooperative networks subject to Nakagami-m fading when the channel state information (CSI) is known at the receiver but is not necessarily ideal. This non-ideality may be due to a feedback delay caused by the difference between the instantaneous CSI during the transmission and the CSI at the time of relay selection, resulting in outdated CSI phenomena. The impact of the outdated CSI on the proposed scheme is well investigated. A closed-form expression for the exact outage probability is derived as well as its asymptotic expression in the high signal-to-noise (SNR) regime. Moreover, upper bounds on the bit-error rate (BER) are presented and a study of the diversity order reveals that for ideal CSI, full diversity in the number of relays and fading parameters m is achieved as opposed to outdated CSI where the achievable diversity is equivalent to the diversity of a coded cooperative network with a single relay.

This paper introduces a relaying scheme of combining cellular networks to establish the relay selection mechanism in the heterogeneous cooperative network model, then based on the system capacity analysis, propose an optimal relay selection scheme with the constraint of the specific outage probability and power allocation. And the multi-hop nodes can act as cooperative mobile relays to ensure the normal communication, to save costs and energy consumption caused by deploying a large number of fixed relays. Simulation results show that the proposed relay node selection algorithm can guide how to dispose the fixed number of relays in the cell and how to arrange these relays to improve the performance of the ergodic capacity of the system.

This paper investigates the integration of relay-assisted Internet of Things (IoT) systems, focusing on the use of multiple relays to enhance the system performance. The central metric of interest in this study is system outage probability, evaluated in terms of latency. Our research provides a comprehensive analysis of system outage probability, considering different relay selection criteria to optimize the system’s transmission performance. Three relay selection strategies are employed to enhance the system transmission performance. Specifically, the first strategy, optimal relay selection, aims to identify the relay that minimizes the latency and maximizes the data transmission reliability. The second approach, partial relay selection, focuses on selecting a subset of relays strategically to balance the system resources and achieve the latency reduction. The third strategy, random relay selection, explores the potential of opportunistic relay selection without prior knowledge. Through a rigorous investigation, our paper evaluates the impact of these relay selection criteria on the performance of relay-assisted edge computing systems. By assessing the system outage probability in relation to latency, we provide valuable insights into the trade-offs and advantages associated with each selection strategy. Our findings contribute to the design and optimization of reliable and efficient edge computing systems, with implications for various applications, including the IoT and intelligent data processing.