Opportunistic Relay Research Articles

Distributed transmission and optimization of relay-assisted space-air-ground IoT systems

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.

Coordination-free Safety Messages Dissemination Protocol for Vehicular Networks

Many vehicular safety applications depend on the rapid and reliable dissemination of safety messages to vehicles at risk. In order to allow sufficient reaction time for emergency events in adverse driving and road conditions, disseminating safety messages over multi-hop vehicles is often needed. However, owing to the capacity limitation of the shared control channel, disseminating safety messages in highly mobile and dynamic vehicular network conditions is challenging. In this article, a Zero-Coordination Opportunistic Routing (ZCOR) algorithm is proposed to deliver mission-critical life safety messages over limited target geocast regions. ZCOR is scalable and robust over dynamic VANET conditions with low rebroadcast overhead. In addition, ZCOR exploits neighbor knowledge for coordinationfree opportunistic packet relay using the novel concept of Circle of Trust (CoT), which defines the range of reliable local neighbor knowledge collection. The performance of ZCOR is evaluated through extensive and realistic simulations capturing time-correlated vehicular channel characteristics.

Opportunistic Relaying Technique over Rayleigh Fading Channel to Improve Multicast Security

Opportunistic Relaying Technique over Rayleigh Fading Channel to Improve Multicast Security

Vehicle-cluster-based opportunistic relays for data collection in intelligent transportation systems

Intelligent transportation system (ITS) is envisioned to greatly improve traffic and enhance safety on roads. ITS relies on a huge amount of data generated from roadside sensor devices to make decisions. Due to the limited channel resources, the base station (BS) that connects with an ITS server can only collect data from parts of sensor devices at a time. To improve the number of device associations, we regard vehicle clusters as relays to collect data, which can avoid high capital expenditure and operating expenses from dedicated relays. Due to the frequently varying channel interference and the limited communication coverage of a vehicle cluster relay (VCR), it is challenging to guarantee the transmission rates and the fairness of sensor devices, which will affect the decisions of ITS. For this reason, we propose a Movement- and Fairness-Aware Heuristic (MFAH) algorithm to tackle the above challenges. MFAH sequentially conducts two novel channel allocation schemes, i.e., exclusive channel allocation scheme and compatible channel allocation scheme, to fast allocate channels and improve the channel utilization, which increases the number of device associations while guaranteeing the transmission rates. Regarding the fairness of each device’s associations, we propose a device association scheme based on the cumulative number of device associations and the distance from the target VCR to select appropriate sensor devices to upload data. We theoretically analyze the lower bound of the obtained network utility. Extensive simulations show that compared with benchmarks, the proposed MFAH algorithm converges fast and effectively improves the network utility (i.e., increasing the number of device associations while guaranteeing the fairness of device associations).

Performance of Spectrum Sharing in Hybrid Satellite Terrestrial Network with Opportunistic Relay Selection

In this paper, we consider the uplink of a hybrid satellite-terrestrial spectrum sharing system, in which satellite terminal communicates with satellite through terrestrial relay-assisted transmission. To accommodate expanding networks within limited spectrum, spectrum sharing is considered a promising candidate. For the system in which satellite terminals and terrestrial terminals share spectrum, we propose opportunistic relay selected spectrum sharing method based on decoding and forwarding protocol. Selecting the optimal relay station is aimed at minimizing the outage probability of the satellite terminal and maximizing the throughput of the system. Due to spectrum sharing policy and imperfections in the RF front end, we also consider the effects of cochannel interference (CCI) and hardware impairments (HIs). The satellite link is modeled as Shadowed-Rician fading, and the terrestrial link uses Nakagami-m fading. In addition, we deduce the closed-form analytical expressions of the satellite terminal outage probability, deduce the asymptotic expressions under the condition of high signal-to-noise ratio, and analyze their achievable diversity orders. Numerical and simulation results validate the performance gain of opportunistic relay selection compared to partial relay selection. Monte Carlo simulations confirm the correctness of the theoretical analysis and illustrate the effects of CCI and HIs on the system.

Outage analysis of cognitive communication system using opportunistic relay selection and secondary users as relays

ABSTRACT Efficient bandwidth utilisation is significant in new communication systems where secondary users can be used besides primary users considering interference issues and idle state of primary users. Using secondary users as relays to transmit their own signals in addition to the primary signals can be applied for more reliability of the system where opportunistic relay selection can significantly enhance the performance of the system. The best-condition secondary user is selected as the optimum relay for retransmission of primary/secondary signal. Outage probability is analysed in this paper based on decode and forward technique in secondary users while the closed-form statement for outage probability is provided and verified by numerical evaluations.

Analysis of Opportunistic Relaying and Load Balancing Gains Through V2V Clustering

Recent advances in digitization, artificial intelligence, and wireless networking are revolutionizing the traditional transportation networks and the automotive industry, leading for instance to the widespread adoption of ride-sharing services and the emergence of self-driving vehicles. As a result, a considerable rise in the volume of infotainment data consumed by the vehicles’ passengers is expected. To support such traffic loads, we explore leveraging vehicles as part of the cellular infrastructure. This paper investigates and quantifies the performance gains that using Vehicle-to-Vehicle (V2V) communication to form relay clusters would enable, including (1) improving opportunistic channel access to the cellular infrastructure by relaying the cluster’s traffic through the vehicle seeing the best channel quality; and (2) balancing traffic loads across cells through cluster multihoming. We introduce a stochastic geometric model allowing us to provide a deeper understanding of the possible gains associated with cluster-based opportunistic relaying and its sensitivity to the system parameters, e.g., base station density, vehicle density on the roads, etc. We develop a natural network utility maximization problem to serve as a baseline to evaluate the performance of a simpler distributed cluster management algorithm which we show to be near-optimal. Overall the results suggest that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10-20\times$</tex-math></inline-formula> gains in the vehicles’ shared rate can be achieved along with significant fairness improvements, while other mobile devices also benefit from the proposed network architecture.

Secure and Reliable Transmission in mmWave NOMA Relay Networks With SWIPT

In this article, we consider the millimeter-wave simultaneous wireless information and power transfer nonorthogonal multiple access (NOMA) relay networks in the presence of multiple passive eavesdroppers, where the near and far Internet of Things (IoT) devices with different communication requirements are served by one source with the help of the relays, and stochastic geometry is used to characterize the distribution of multiple nodes. First, a NOMA pairing and relay selection scheme is designed. Then, the closed-form expressions for the energy-information coverage probability (EICP) and the effective secrecy throughput of the near IoT devices are derived. Finally, the EICPs of the far IoT device under random relay selection and opportunistic relay selection schemes are obtained. Moreover, the asymptotic expressions of the EICP for both the near and far IoT devices are derived, which show that the asymptotic EICP when the number of antennas at the source or relay tends to infinity is only dependent on the location distribution of nodes and blockage environment. The simulation results show that NOMA can outperform orthogonal multiple access, and the advantage of the opportunistic relay selection scheme over the random relay selection scheme is more obvious when the density of the relay is relatively large.

An Optimized Distributed Routing Protocol for Energy Management Systems Based on Wireless Sensor Networks in Intelligent and Smart Structures

Energy and spectrum efficiency for energy management systems based on wireless sensor networks in intelligent structures and powered by ambient energy harvesting (EH) are the main problems in wireless sensor networks. Herein, we consider relay selection methods. To address this issue, we proposed the optimal multiantenna power beacon opportunistic relay selection (OMPB-ORS) protocol, which uses decoding and forward methods, in which the relay wireless sensor nodes and the second source are energy-restricted and can harvest energy from a power beacon (PB) multiantenna to transmit aggregated information data from source to destination. The proposed protocol based on specific s witching t ime r eceiver a rchitecture e nhances e nd-to-end p erformance f or m aximum h ardware impairments and interference for the transceiver. To evaluate the performance, we compared our proposed protocol with best ORS (B-ORS), conventional ORS (C-ORS), and hybrid partial relay selection (H-PRS) protocols. Using the Rayleigh-fading channel, the simulation is driven based on asymptotic and exact form expressions of throughput (TP) and outage probability (OP). Simulation results show that the OMPB-ORS protocol achieves a higher TP and OP than all compared protocols.

Outage Performance of Multi-UAV Relaying-Based Imperfect Hardware Hybrid Satellite-Terrestrial Networks

In this paper, we consider an imperfect hardware hybrid satellite-terrestrial network (HSTN) where the satellite communication with a ground user equipment (UE) is aided by the multiple amplify-and-forward (AF) three-dimensional ($3$D) mobile unmanned aerial vehicle (UAV) relays. Herein, we consider that all transceiver nodes are corrupted by the radio frequency hardware impairments (RFHI). Further, a stochastic mixed mobility (MM) model is employed to characterize the instantaneous location of $3$D mobile UAV relays in a cylindrical cell with UE lying at its center on ground plane. Taking into account the aggregate RFHI model for satellite and UAV relay transceivers and the random $3$D distances-based path loss for UAV relay-UE links, we investigate the outage probability (OP) and corresponding asymptotic outage behaviour of the system under an opportunistic relay selection scheme in a unified form for shadowed-Rician satellite links' channels and Nakagami-\emph{m} as well as Rician terrestrial links' channels. We corroborate theoretical analysis by simulations.

An approach of flow compensation incentive based on Q-Learning strategy for IoT user privacy protection

In MCS (mobile crowd sensing), reducing network overhead, protecting IoT user privacy and increasing the participation enthusiasm of perception task are key issues. The QLPPIA (an incentive approach of flow offset based on Q-Learning algorithm for perception user privacy protection) was proposed. A system model that combined MCS with MEC (mobile edge computing) was designed. The edge center uploaded the perception results to the MCS cloud declining its cloud overhead. A privacy protection structure of attribute relevance based on Markov chain Monte Carlo was constructed, which can protect the privacy data. Perception outcomes with higher accuracy of attribute relevance were generated. An incentive pattern of flow offset for user privacy protection based on Q-Learning opportunistic cooperation transfer was designed to cut down MCS cloud flow offset cost and facilitate user enthusiasm. Compared with the existing private protection of high-dimensional attribute data, opportunistic relay perception incentive, and other solutions, the QLPPIA method improves the perception result precision by 27.06%, increases MCS cloud cost of 88.80%, and declines flow compensation expenditure at 19.03% on average.

Half-Duplex and Full-Duplex Performance Comparison for Different Fading Channel Using HMR Protocol in MIMO Technology

This paper deals with the performance of Half Duplex (HD) and Full Duplex (FD) in different fading channels via relay networks. A new Heterogeneous Multiplex Relay (HMR) protocol is proposed for the achievement of spectrum efficiency over Multiple Input and Multiple Output (MIMO) using HD and FD. The Key idea of the protocol the relay selection among half duplex and full duplex for overcoming fading which achieves diversity and multiplexing gain. The protocol is projected in Massive MIMO with Opportunistic Relay Selection which requires limited feedback/signaling for relay and operation mode selection. The max-min criteria help in finding the best channel which leads to the best relay selection. Consideration of the Coded Cooperation and Successive Interference Cancellation helps recovery of the loss of Multiplexing Gain. Simulation result shows the throughput performance of Heterogeneous Multiplex Relay (HMR) protocol compared to HD and FD. HMR protocol provides 80% capacity performance due to its allotted channels between HD and FD. It also shows the performance of Bit Error Rate (BER) vs Signal to Noise Ratio (SNR) values compared to Rayleigh, Rician, and Nakagami Fading Channels.

Joint User Scheduling, Relay Selection, and Power Allocation for Multi-Antenna Opportunistic Beamforming Systems.

Opportunistic beamforming (OBF) is a potential technique in the fifth generation (5G) and beyond 5G (B5G) that can boost the performance of communication systems and encourage high user quality of service (QoS) through multi-user selection gain. However, the achievable rate tends to be saturated with the increased number of users, when the number of users is large. To further improve the achievable rate, we proposed a multi-antenna opportunistic beamforming-based relay (MOBR) system, which can achieve both multi-user and multi-relay selection gains. Then, an optimization problem is formulated to maximize the achievable rate. Nevertheless, the optimization problem is a non-deterministic polynomial (NP)-hard problem, and it is difficult to obtain an optimal solution. In order to solve the proposed optimization problem, we divide it into two suboptimal issues and apply a joint iterative algorithm to consider both the suboptimal issues. Our simulation results indicate that the proposed system achieved a higher achievable rate than the conventional OBF systems and outperformed other beamforming schemes with low feedback information.

Opportunistic DF-AF Selection Relaying in Hybrid Wireless and Power Line Communication for Indoor IoT Networks

This manuscript investigates the system performance of hybrid wireless and power line communication networks for indoor Internet of Things applications. Differentiating itself from the existing literature, the performance of the direct link and dual-hop energy harvesting relay-aided links is analyzed under the condition of indoor fading modeled by log-normal distribution. Moreover, the manuscript presents the analytical expressions of the successful transmission probability of the deployed opportunistic decode-and-forward and amplify-and-forward relay selection scheme, and validates them with Monte Carlo simulations. Moreover, the impact of different system parameters on the successful transmission probability is revealed. For the considered hybrid system, in general, the opportunistic decode-and-forward relaying scheme outperforms the opportunistic amplify-and-forward relaying scheme. As importantly, increasing the source to relay distance and power splitting ratio over certain limits significantly deteriorates the system performance, indicated by the decrease in the successful transmission probability.

Physical layer secrecy performance analysis of relay selection in a cooperative wireless network

This paper investigates the performance of physical (PHY) layer secrecy in a cooperative relaying with opportunistic relay selection, where an eavesdropper intercepts the transmit signals between the authorized users. At first, theoretical expressions are derived for three performance criteria for evaluating the PHY security, namely: the secrecy outage probability, the average of secrecy capacity, and the probability of non-zero secrecy capacity. Then the secrecy performance in information transmissions is investigated. Moreover, using the computer simulations, the validity of the derived expressions and the carried out analyses are examined and verified. To show the enhancement on the secrecy performance in the presented system that employs opportunistic relay selection, the secrecy outage probabilities of the opportunistic relay selection system, one relay cooperation system, and direct transmission system are also compared.

Cooperative Relaying in a SWIPT Network: Asymptotic Analysis Using Extreme Value Theory for Non-Identically Distributed RVs

This paper derives the distribution of the maximum end-to-end (e2e) signal to noise ratio (SNR) in an opportunistic relay selection based cooperative relaying network having a large number of non-identical relay links. The source is simultaneous wireless information and power transfer enabled, and the relays are capable of both time splitting (TS) and power splitting (PS) based energy harvesting (EH). Contrary to the majority of literature in communication, which uses extreme value theory (EVT) to derive the statistics of extremes of sequences of independent and identically distributed random variables (RVs), we demonstrate how EVT can be used to derive the maximum statistics of sequences of independent and non-identically distributed normalised SNR and hence the distribution of the maximum SNR. Using these results, we derive simple expressions for evaluating the outage capacity, and achievable throughput at the destination. Finally, we present the utility of the results for deciding the optimum TS and PS factors of the hybrid EH relays that maximise outage capacity, and achievable throughput at the destination. Furthermore, we establish the stochastic ordering of the e2e SNR, which in turn allows the characterisation of the variations in the e2e performance with respect to the variations in different system parameters.

Outage probability analysis of overlay cognitive two‐way relaying scheme with opportunistic relay selection

The authors investigate an overlay cognitive two-way relaying system where max-min (MM) relay selection scheme is employed for improving the reliability of the considered system. Furthermore, they design the process of the data forwarding and relay selection in the overlay cognitive two-way relaying system. Based on the MM relay selection criterion, the exact close-form expression of outage probability is derived. From numerical simulations, it is observed that there is an outage probability floor appearing in the high signal-to-noise ratio (SNR) region, and the reason for its occurrence is stated. Besides, the approximate result of outage probability in high SNR is provided, which shows that the ratio of interference channel' transmit power and main channel' transmit power will not affect the outage probability in low SNR region, but it will significantly affect it in the high SNR region. Although each individual channel state information (CSI) will not be able to control the outage performance of this considered system in the high SNR region, the ratio of each channel's CSI will be able to do the same.

Short-Packet Communications in Wireless-Powered Cognitive IoT Networks: Performance Analysis and Deep Learning Evaluation

In this paper, we study short-packet communications in wireless-powered cognitive Internet-of-Things (IoT) networks with multiple primary receivers (PRs). The considered system can be applied for small factory automations, where a source and multiple relays harvest energy from a multi-antenna dedicated power beacon (PB) to send short packets to a robot destination for controlling purposes under cognitive radio constraint imposed by PRs. We propose an opportunistic relay selection (ORS) scheme to maximize the end-to-end signal-to-noise ratio in cognitive IoT systems. Closed-form expressions for the average block error rate (BLER) of the proposed system are obtained, based on which the performance floor analysis, goodput, and energy efficiency (EE) are also carried out. Relying on analytical results, we develop a deep learning framework for the BLER prediction with high accuracy and short execution time. Simulation results show the BLER, goodput, and EE improvements of the ORS scheme over conventional relay selection schemes. Moreover, the developed deep learning-based evaluation model achieves the equivalent performance as the ORS scheme in terms of BLER, goodput, and EE, while remarkably reducing the execution time in cognitive IoT systems.

A Simple Cooperative Diversity Method Based on Deep-Learning-Aided Relay Selection

Opportunistic relay selection (ORS) has been recognized as a simple but efficient method for mobile nodes to achieve cooperative diversity in slow fading channels. However, the wrong selection of the best relay arising from outdated channel state information (CSI) in fast time-varying channels substantially degrades its performance. With the proliferation of high-mobility applications and the adoption of higher frequency bands in 5G and beyond systems, the problem of outdated CSI will become more serious. Therefore, the design of a novel cooperative method that is applicable to not only slow fading but also fast fading is increasingly of importance. To this end, we develop and analyze a deep-learning-aided cooperative method coined predictive relay selection (PRS) in this article. It can remarkably improve the quality of CSI through fading channel prediction while retaining the simplicity of ORS by selecting a single opportunistic relay so as to avoid the complexity of multi-relay coordination and synchronization. Information-theoretic analysis and numerical results in terms of outage probability and channel capacity reveal that PRS achieves full diversity gain in slow fading wireless environments and substantially outperforms the existing schemes in fast fading channels.

Combining Power Allocation and Superposition Coding for an Underlay Two-way Decode-and-forward Scheme

Combining Power Allocation and Superposition Coding for an Underlay Two-way Decode-and-forward Scheme