Beamforming and Interference Alignment Transmission Mechanism Based on Optimal Relay Selection

The optimal relay selection problem in multiuser cooperative wireless networks is considered in this paper. A general discrete time model for such networks is introduced which takes into account the dynamic variations of the channel state as well as stochastic arrival of data packets into the system. The model consists of a set of mobile users, one destination node and R relay nodes which may be either mobile or fixed. The system uses the benefit of cooperative diversity by relaying in decode and forward or amplify and forward mode. We assume that each user either transmits its packets directly to the destination or selects a relay node to cooperatively transmit its packets. It is not however trivial whether a user at each time slot has to cooperate with any relay node or not and if so, which relay node should be selected for cooperation. We will propose a throughput optimal relay selection policy that can stabilize the system for all the arrival rate vectors strictly inside the stability region. Then, we show that the optimal policy is equivalent to finding the maximum weighted matching in a weighted bipartite graph at each time slot. We also use simulations to compare the performance of the throughput optimal relay selection strategy with an instantaneous throughput optimal policy as well as a non-cooperative policy in terms of average queue occupancy (or equivalently, queueing delay).

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.

Physical-layer network coding (PNC) promises a significant gain In overall network throughput for multi-user cooperative communications. In a multi-unicast scenario, one drawback associated with PNC is an additional noise term, coined as network coding (NC) noise, which severely degrades the system data rate. In this paper, our contribution to address this challenging problem is source and relay power control with the objective of maximization of the minimum average achievable rate among all the source-destination pairs subject to a given total power constraint. We further develop a joint power allocation and relay selection scheme, which only rely on long-term channel statistics, to extend our results to general network topologies. We show that the joint optimization problem can be divided into two problems: optimal power allocation and optimal relay selection where the former is scalable and leads to a power assignment algorithm that exhibits the same optimization complexity for any number of sources in the network and the latter can be performed in a decentralized manner. By means of simulations, we validate our theoretical developments and verify the efficiency of our algorithm in improving the average achievable rate compared to a multi-unicast system with no power control or relay selection. We conclude that the proposed algorithm largely combats the adverse effects of NC noise while achieving near optimal fairness.

This work considers the relay selection and resource allocation problem (i.e., link scheduling, and rate allocation) for multi-source, multi-relay dual-hop wireless networks. The relays employ buffers to store the received data from the sources for future transmissions. End-to-end (E2E) delay of each traffic flow originated from a source or a relay is constrained in terms of maximum allowable delay-outage probability. To solve this problem, we first study the resource allocation problem to maximize the constant supportable arrival rate of a non-prioritized source under minimum rate requirements of the prioritized sources and relays for a given relay selection solution. Then, the optimal relay selection can be determined to support the largest rate of the non-prioritized source among all possible relay selection solutions. We derive the resource allocation solutions using asymptotic delay analysis and convex optimization techniques. We also develop an online allocation algorithm which does not require the knowledge of the fading statistics by using stochastic approximation theory. Numerical results are presented to demonstrate the usefulness of the proposed resource allocation design for relay selection under different delay and rate constraint regimes.

A novel cross-layer joint relay selection and power allocation (CL-JRSPA) scheme over physical layer and data-link layer is proposed for cooperative relaying system in this paper. Our goal is finding the optimal relay selection and power allocation scheme to maximize system achievable rate when satisfying total transmit power constraint in physical layer and statistical delay quality-of-service (QoS) demand in data-link layer. Using the concept of effective capacity (EC), our goal can be formulated into an optimal joint relay selection and power allocation (JRSPA) problem to maximize the EC when satisfying total transmit power limitation. We first solving optimal power allocation (PA) problem with Lagrange multiplier approach, and then solving optimal relay selection (RS) problem. Simulation results demonstrate that CL-JRSPA scheme gets larger EC than other schemes when satisfying delay QoS demand. In addition, the proposed CL-JRSPA scheme achieves the maximal EC when relay located approximately halfway between source and destination, and EC becomes smaller when the QoS exponent becomes larger.

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.

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.

Energy efficient resource allocation based on relay selection and subcarrier pairing with channel uncertainty in cognitive radio network

In this paper, a cooperative non-orthogonal multiple access (NOMA) vehicle communication system in urban scenarios is studied. Max-min optimal relay selection strategy is adopted to derive the closed-form expressions of channel capacity and interruption probability for the target vehicle users. In the simulation, the influence of relay number, road loss, power allocation and destination vehicle distance on the system is considered, and the proposed max-min optimal relay selection strategy is compared with three relay selection strategies, namely Max-SR, Max-RD and random relay. The results show that the proposed max-min optimal relay selection strategy achieves the better user performance of destination vehicle.

In this paper, we consider the optimal relay selection policy for decode-and-forward opportunistic relaying systems under the assumption that the channel gain of the source-destination link is good-enough to produce some improvement in the end-to-end performance over the relay channels. The optimal relay selection policy shows that the conventional relay selection policy that appeared in the literature is suboptimal. We derive the exact expression for the end-to-end outage probability over Rayleigh fading channels. In addition, we look into the asymptotic high signal-to-noise ratio (SNR) regime, and characterize the diversity order and coding gain. Our findings reveal that the new optimal relay selection policy outperforms the suboptimal relay selection policy via coding gain while both policies have the same diversity order. We provide simulation results to verify the validity of our theoretical analysis.

With the advent of sensor nodes with higher communication and sensing capabilities, the challenge arises in forming a data gathering network to maximize the network capacity. The channel sharing for higher data transmission leads to interfering problems. The effects of interferences become increasingly important when simultaneous transmissions are done in order to increase wireless network capacity. In such cases, achieving a high throughput and low delay is difficult. We propose a new method that uses interference alignment (IA) technique to mitigate interference effects in Wireless Sensor Networks (WSNs). In IA technique, multiple transmitters jointly encode their signals to intended receivers such that interfering signals are separated and eliminated. Simulation results demonstrate that compared to TDMA algorithms, the proposed method significantly increases the performance of the network delay and throughput by reducing the delay and increasing throughput.

New applications associated with the Internet of Things (IoT) often involve cooperation and relaying among many autonomous wireless devices. This should be supported by wireless transmission schemes in physical layer. Different from half-duplex (HD) cooperative networks, the relay and destination in full-duplex (FD) cooperative networks suffer from the loop interference and the direct link interference respectively, since all the nodes work on the same frequency band simultaneously. In this paper, we first investigate the relay selection strategies by taking the direct link interference into consideration. Then, we analyze the outage probabilities of relay selection schemes for FD cooperative networks under amplify-and-forward (AF) and decode-and-forward (DF) protocols. Numerical simulations are performed to verify the analytical expressions and make a comparison between the proposed selection schemes and the conventional schemes. It is shown that significant performance gain can be achieved by the proposed schemes compared with the conventional schemes without consideration of the direct link interference, especially in high signal-to-noise ratio (SNR) regime.

This paper focuses on the problem of selecting the optimal common node (CN) in a wireless sensor network to serve as the relay to aid the data transmission between the cluster head (CH) and the data fusion center (DFC). Optimal relay selection with the objective of minimizing the outage probability is a difficult problem which depends on multiple factors. In this paper, an outage-optimal relay selection algorithm using fuzzy comprehensive evaluation is proposed. The algorithm takes into consideration both the channel state information and the cooperation power information of the nodes, and uses fuzzy comprehensive evaluation to select the optimal relay. The optimum fuzzy weight, which guarantees the optimality of the proposed relay selection algorithm in terms of the outage probability, is specified using general-purpose iterative methods. Simulation results show that the proposed relay selection algorithm evidently outperforms the algorithm based only on the channel state information in terms of the outage probability.

In recent years, several experimental studies have come out to validate the theoretical findings of interference alignment (IA), but only a handful of studies have focused on blind interference alignment. Unlike IA and other interference mitigation techniques, blind IA does not require channel state information at the transmitter (CSIT). The key insight is that the transmitter uses the knowledge of channel coherence intervals and receivers utilize reconfigurable antennas to create channel fluctuations exploited by the transmitter. In this work, we present a novel experimental evaluation of a reconfigurable antenna system for achieving blind IA. We present a blind IA technique based on reconfigurable antennas for a 2-user multipleinput single-output (MISO) broadcast channel implemented on a software defined radio platform where each of the receivers is equipped with a reconfigurable antenna. We further compare this blind IA implementation with traditional TDMA scheme for benchmarking purposes. We show that the achievable rates for blind IA can be realized in practice using measured channels under practical channel conditions. Additionally, the average error vector magnitude and bit error rate (BER) performances are evaluated.

In this paper, we study the secure communication of dual-hop cognitive relaying networks. An eavesdropper can combine two received signals from two hops by using the maximum ratio combining technique. The data transmission from the secondary source to the secondary destination is assisted by the best decode-and-forward relay, which is selected from four relay selection schemes. The first scheme, MaSR, is based on the maximum channel gain from the source to the relays. In the second scheme, MaRD, the best relay is selected on the basis of the maximum channel gain from the relays to the destination. In the third scheme, MiRE, the gain to the eavesdroppers is instead minimized. Finally, optimal relay selection is considered as the fourth scheme. For these four schemes, we study the system security performance by deriving the exact analytical secrecy outage probability. These analytical expressions are then verified by comparing them with the results of Monte Carlo simulations. Herein, we evaluate and discuss the outage performance of the schemes while varying important system parameters: the number and locations of the relay nodes, primary user node, and eavesdropper; the transmit power threshold; and the target secure rate.