Multiple Relay Selection Scheme Research Articles

Joint Lifetime-Outage Optimization in Relay-Enabled IoT Networks—A Deep Reinforcement Learning Approach

Network lifetime maximization in Internet of things (IoT) is of paramount importance to ensure uninterrupted data transmission and reduce the frequency of battery replacement. This letter deals with the joint lifetime-outage optimization in relay-enabled IoT networks employing a multiple relay selection (MRS) scheme. The considered MRS problem is essentially a general nonlinear 0-1 programming which is NP-hard. In this work, we use the application of the double deep Q network (DDQN) algorithm to solve the MRS problem. Our results reveal that the proposed DDQN-MRS scheme can achieve superior performance than the benchmark MRS schemes.

CSI Based Multiple Relay Selection and Transmit Power Saving Scheme for Underlay CRNs Using FRBS and Swarm Intelligence

In this article, a multiple relay selection (MRS) scheme for signal-to-noise ratio (SNR) enhancement is proposed for underlay relay-assisted cognitive radio networks (RCRNs). A secondary source-destination pair experiencing deep fading on direct path is assisted by amplify-and-forward (AF) relays in an underlay mode. In this energy-constrained scenario, the aim is to maximize the secondary network's end-to-end SNR through an intelligent power-saving method incorporated with MRS. In contrast to the prior relay selection (RS) schemes, the relay-selection factor is the difference of SNR of the source-relay link and corresponding relay-destination link for each relay along with its corresponding interference channel coefficient. The difference factor aims to achieve the SNR upper bound while performing minimum power amplification, eventually resulting in interference mitigation as well. The proposed algorithm has been implemented using Fuzzy Rule Based System (FRBS), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and their performance has been compared through simulations.

A multiple relay selection scheme based on QPO in cognitive relay networks

Cognitive relay networks can increase the channel gain of wireless transmission and strengthen the anti-fading ability of the channel. It has recently been considered as an effective way to improve the throughput of cognitive radio system. Therefore, determining the appropriate relay selection scheme is of vital importance to improve the quality of communication. In this paper, we study the difficulty of multiple relay selection (MRS) in cognitive relay networks (CRNs). Considering the scenario of spectrum sharing, we adopt simple power control strategy to limit the power of secondary sources and relays in order to satisfy the interference constraint. To get a better solution for the discrete MRS problem in CRNs, we propose a novel intelligent algorithm which is named as quantum-inspired physics optimisation (QPO) algorithm. For QPO, the law of gravity, Newton's second law, and quantum mechanism are combined effectively. We have designed three different quantum rotation angles. Based on the quantum mechanism, the convergence rate and the searching ability of the algorithm are improved. The good performance of the proposed scheme in MRS is demonstrated according to the simulation results.

Joint Multiple Relay Selection and Time Slot Allocation Algorithm for the EH-Abled Cognitive Multi-User Relay Networks

The wireless energy harvesting (EH) technique is regarded as a new way to provide an energy supply for energy-constrained cognitive relay networks (CRNs). A novel wireless EH cognitive multi-user relay network (CMRN) for the underlay protocol is investigated in this paper. In this system, there are multiple primary users (PUs) and multiple secondary users (SUs). The SUs can share the licensed spectrum and harvest energy from ambient signals. The problems of multiple relay selection by the SUs and of finding the optimal EH ratio are considered. We analytically derive the exact expression of the throughput of a secondary network. In it, there are four constraints: for the permitted peak interference with each primary transmitter (PT); for the sum interference for each PT; that the transmit power of secondary source nodes (SSNs) and secondary relays (SRs) should be less than the energy harvested; and that each secondary source node/secondary destination node (SSN-SDN) pair can only choose one SR. To obtain the optimal performance of the secondary network’s throughput, we should optimize the multiple relay selection scheme and the EH ratio. Actually, it is a classic integer optimization problem to design an optimal multiple relay selection scheme. However, the selection of the optimal EH ratio is a continuous optimization problem. The joint multiple relay selection and time slot allocation is a classical hybrid optimization problem. So, we propose a novel quantum sine cosine algorithm (QSCA) for resolving the difficulty with optimization of multiple relay selection and the EH ratio. Our simulation results verify our proposed solution by showing the influence of different parameters for the proposed model and by demonstrating good performance under the QSCA.

A multiple relay selection scheme based on QPO in cognitive relay networks

Cognitive relay networks can increase the channel gain of wireless transmission and strengthen the anti-fading ability of the channel. It has recently been considered as an effective way to improve the throughput of cognitive radio system. Therefore, determining the appropriate relay selection scheme is of vital importance to improve the quality of communication. In this paper, we study the difficulty of multiple relay selection (MRS) in cognitive relay networks (CRNs). Considering the scenario of spectrum sharing, we adopt simple power control strategy to limit the power of secondary sources and relays in order to satisfy the interference constraint. To get a better solution for the discrete MRS problem in CRNs, we propose a novel intelligent algorithm which is named as quantum-inspired physics optimisation (QPO) algorithm. For QPO, the law of gravity, Newton's second law, and quantum mechanism are combined effectively. We have designed three different quantum rotation angles. Based on the quantum mechanism, the convergence rate and the searching ability of the algorithm are improved. The good performance of the proposed scheme in MRS is demonstrated according to the simulation results.

Performance analysis of relay subset selection schemes for underlay relay‐assisted CRNs

In underlay cognitive radio networks (CRNs), secondary users (SUs) are allowed to co-exist with the primary users at the cost of reduced transmit power in order to satisfy the stringent interference constraint. This obligation reduces the coverage area of the SUs and they have to involve relaying services for assistance. However, selecting the best combination of relays from the available options is more challenging in an energy-constrained environment, since it is affected not only by the interference constraint, but also the selected subset of relays must guarantee some quality-of-service (QoS) at the secondary destination also. This study is focused on an amplify-and-forward-based relay-assisted CRN operating in an underlay scenario and studies three relay subset selection or multiple relay selection schemes taking into consideration outgoing secondary and primary link qualities of each candidate relay. For each scheme, the closed-form expression for probability density function of signal-to-noise ratio at the secondary destination is derived followed by detailed analysis of two QoS metrics, i.e. outage probability and bit error rate. Finally, simulations have been performed to validate the analytical results.

Improving Bivious Relay Selection in Vehicular Delay Tolerant Networks

In Vehicular Delay Tolerant Networks, a number of Roadside Units (RSUs) are deployed along the road and connected to the infrastructure network to provide various services to the vehicles on the road. However, it is hard to cover the long highways completely, due to the deployment cost. In such uncovered areas between two neighboring RSUs, a connection between a vehicle and an RSU cannot be established. To cope with this, few schemes have been proposed recently, enabling one RSU to select one relay vehicle to provide continuous communications for the vehicle moving in the uncovered area. However, the selection of an appropriate relay vehicle for pre-storing maximum data is an open issue. In this paper, we, therefore, propose an adaptive multiple-relay selection scheme that allows RSU to select relay vehicles while taking most relevant multiple criteria into the account. The relay selection triggers when a vehicle is unable to receive all the requested data from the corresponding RSU. The simulation results show that our scheme enables vehicles to retrieve maximum amount of the requested data in uncovered areas.

Optimization of a Power Splitting Protocol for Two-Way Multiple Energy Harvesting Relay System

Energy harvesting (EH) combined with cooperative communications constitutes a promising solution for future wireless technologies. It enables additional efficiency and increased lifetime to wireless networks. This paper investigates a multiple-relay selection scheme for an EH-based two-way relaying (TWR) system. All relays are considered EH nodes that harvest energy from renewable energy and radio frequency (RF) sources. Some of them are selected to forward data to the destinations. The power splitting (PS) protocol, by which the EH node splits the input RF signal into two components for EH and information transmission, is adopted at the relay nodes. The objective is to jointly optimize: 1) the set of selected relays; 2) their PS ratios; and 3) their transmit power levels in order to maximize data rate-based utilities over multiple coherent time slots. A joint-optimization solution based on geometric programming (GP) and binary particle swarm optimization is proposed to solve non-convex problems for two utility functions reflecting the level of fairness in the TWR transmission. Numerical results illustrate the system’s behavior versus various parameters and show that the performance of the proposed scheme is very close to that of the optimal branch-and-bound method and that GP outperforms the dual problem-based method.

Multiple Criteria Relay Selection Scheme in Cooperative Communication Networks

This paper considers a wireless cooperative network with a base station (central unit) and many subscribers (users) in which the subscribers have the ability to relay information for each other to improve the overall network performance. In future wireless communication networks where subscribers are intellectual and pursue various objectives, they will not help relay information for others. This means that the viability of cooperative communication networks largely depends on the willingness of users to help. The reputation based schemes solved this problem by stimulating the users to cooperate with others. Besides, the average achievable rate at the destination node in a relay based network highly depends on the relay node location. Therefore, for a relay selection scheme, the choices of relay location, and the reputation of each user as well as signal-to-noise ratio, which is the main criterion for relay selection schemes, are important selection parameters. This paper proposes a novel multiple criteria relay selection scheme with a low implementation complexity. The proposed scheme incorporates reputation, SNR and location of the users in a highest-level design that not only selects the best relay node for each source-destination pair, but also assigns weight efficiently for each criterion. A simple and efficient optimization tool based on multiple criteria decision making method is employed to solve our formulated problem. In addition, a novel information theoretic measure, which effectively measures dissimilarity between candidate relay nodes and ideal solutions, is also investigated. Since the proposed scheme determines the potential relay nodes in order of their superiority based on the predetermined criteria, it can be utilized in multiple relay selection schemes in wireless relay networks and also in the indirect reciprocity game methods. Finally, the numerical results are provided to illustrate the comparisons between different typical experiments. To best of our knowledge, no prior work has studied the process of relay selection from this point of view.

Quantum flower pollination algorithm for optimal multiple relay selection scheme

Quantum flower pollination algorithm for optimal multiple relay selection scheme

Quantum flower pollination algorithm for optimal multiple relay selection scheme

In order to obtain optimal selection scheme with multiple source-destination pairs and multiple potential relays in cooperative relay networks, an optimal relay selection scheme is designed in cooperative relay networks considering co-channel interference (CCI). It is an integer optimisation problem for selecting suitable relay nodes to obtain optimal system performance. To get the optimal estimation performance with low computing complexity, quantum flower pollination algorithm (QFPA) is proposed to resolve the difficulties of optimal relay selection, and the proposed optimal relay selection scheme is called as quantum flower pollination algorithm based optimal relay selection (QFPA-ORS). The proposed QFPA combines the advantages of quantum evolutionary theory and flower pollination algorithm (FPA). So QFPA has the capability to search the optimal solution. Simulation results show that QFPA based relay selection scheme has the ability to search global optimal solution compared with other relay selection schemes based on classical algorithm and performs better than three other previous intelligent algorithms.

Adjustable Multiple Relay Selection Based on Steady-State Mean Square Joint Error for Cooperative Communication

In this paper, an adjustable multiple relay selection (MRS) scheme for cooperative communication with amplify-and-forward (AF) relay under frequency selective channels is proposed. In the proposed scheme, the relays are ordered firstly by the steady-state mean square error (MSE), then the relays are sequentially selected out from N relays and the number of cooperating relays is adjusted dynamically according to the steady-state mean square joint error (MSJE). The aim of this work is to dynamically estimate the optimum number N o of cooperating relays. Optimum means the minimum number of cooperating relays, N o , achieving the minimum level of steady-state MSJE. Numerical results verify the analyses and show that the scheme can adaptively adjust the number of cooperating relays, and outperform conventional relay selection schemes. Hence, the proposed scheme provides better tradeoff between BER performance and spectral efficiency and to save more energy in cooperative wireless networks.

Opportunistic Multiple Relay Selection for Two-Way Relay Networks with Outdated Channel State Information

Outdated Channel State Information (CSI) was proved to have negative effect on perfor-mance in two-way relay networks. The diversity order of widely used opportunistic relay selection (ORS) was degraded to unity in networks with outdated CSI. This paper proposed a multiple relay selection scheme for amplify-and-forward (AF) based two-way relay networks (TWRN) with outdated CSI. In this scheme, two sources exchange information through more than one relays. We firstly select N best relays out of all candidate relays with respect to signal-noise ratio (SNR). Then, the ratios of the SNRs on the rest of the candidate relays to that of the Nth highest SNR are tested against a normalized threshold μ[0, 1], and only those relays passing this test are selected in addition to the N best relays. Expressions of outage probability, average bit error rate (BER) and ergodic channel capacity were obtained in closed-form for the proposed scheme. Numerical results and Simulations verified our the-oretical analyses, and showed that the proposed scheme had significant gains comparing with conventional ORS.

Performance Analysis of Relay Subset Selection for Amplify-and-Forward Cognitive Relay Networks

Cooperative communication is regarded as a key technology in wireless networks, including cognitive radio networks (CRNs), which increases the diversity order of the signal to combat the unfavorable effects of the fading channels, by allowing distributed terminals to collaborate through sophisticated signal processing. Underlay CRNs have strict interference constraints towards the secondary users (SUs) active in the frequency band of the primary users (PUs), which limits their transmit power and their coverage area. Relay selection offers a potential solution to the challenges faced by underlay networks, by selecting either single best relay or a subset of potential relay set under different design requirements and assumptions. The best relay selection schemes proposed in the literature for amplify-and-forward (AF) based underlay cognitive relay networks have been very well studied in terms of outage probability (OP) and bit error rate (BER), which is deficient in multiple relay selection schemes. The novelty of this work is to study the outage behavior of multiple relay selection in the underlay CRN and derive the closed-form expressions for the OP and BER through cumulative distribution function (CDF) of the SNR received at the destination. The effectiveness of relay subset selection is shown through simulation results.

Multiple-relay selection in amplify-and-forward cooperative wireless networks with multiple source nodes

In this article, we propose multiple-relay selection schemes for multiple source nodes in amplify-and-forward wireless relay networks based on the sum capacity maximization criterion. Both optimal and sub-optimal relay selection criteria are discussed, considering that sub-optimal approaches demonstrate advantages in reduced computational complexity. Using semi-definite programming convex optimization, we present computationally efficient algorithms for multiple-source multiple-relay selection (MSMRS) with both fixed number and varied number of relays. Finally, numerical results are provided to illustrate the comparisons between different relay selection criteria. It is demonstrated that optimal varied number MSMRS outperforms optimal fixed number MSMRS under the same power constraints.

Joint Relay Selection and Power Allocation for Cooperative Communication over Frequency Selective Fading Channels

In this paper, we consider the joint problem of relay selection and optimal power allocation for multi-relay amplify-and-forward (AF) cooperative communication system over frequency selective fading channels. An optimization model combined relay selection and power allocation under a total transmission power budget is formulated. Then, this combinatorial problem is solved in a distributed strategy. Relay selection with a new threshold-based multiple-relay selection (MRS) scheme is implemented at first, and then power is allocated between source and the selected relays in an optimized way to maximize channel capacity. Simulation result shows that the proposed joint scenario with relay selection and power allocation achieves better throughput performance than that of parallel-relay scenario (means that random relay is selected to forward data and allocated part of total power on average). Furthermore, the performances of the new MRS scheme and other relay selection strategies are also investigated.

Relay Selection Schemes for Cooperative Communications Systems Sensor Networks

Due to being so effective to mitigate the fading effect of wireless channels relay networks have received so much attention recently. Especially because relays are typically small, power limited and low cost and also can remove the problem of attenuation of signal due to propagation loss. Moreover increasing the number of relays improves the system performance and also using more power. The system efficiency can be enhanced by selecting relays in better conditions. In this paper single and multiple relay selection schemes is proposed applying Principal Component Analysis (PCA) method. The main idea of PCA method is selecting relays according to the eigenvector corresponding to the largest eigenvalue of channels from source to the destination. The PCA method provides an acceptable tradeoff between better power and Bit Error Rate (BER) performances. The higher efficiency is achieved by Appling PCA which demonstrated in power performance and this management of total power usage makes relay networks more practical.

A General Diversity Gain Function and Its Application in Amplify-and-Forward Cooperative Networks

The diversity gain function is a unified metric for the asymptotic error performance of wireless communication systems. In this correspondence, we propose a theorem that relates the diversity gain function and the coding gain to the probability density function of the instantaneous signal-to-noise ratio (SNR) at the origin. It provides a general framework for analyzing the asymptotic reliability of wireless communication systems in the presence of fading. As two applications of the proposed theorem, we evaluate two relay selection schemes in fixed-gain amplify-and-forward (AF) cooperative networks. The results show that even if not all channel state information is available at the destination, fixed-gain AF relay selection schemes can still achieve full cooperative diversity and near optimal error performance. This is an outstanding merit that instantaneous-gain AF relay selection schemes do not possess [Y. Jing and H. Jafarkhani, “Single and multiple relay selection schemes and their achievable diversity orders,” IEEE Trans. WIRELESS COMMUN., vol. 8, no. 3, pp. 1414-1423, Mar. 2009].

Single and multiple relay selection schemes and their achievable diversity orders

This paper is on relay selection schemes for wireless relay networks. First, we derive the diversity of many single-relay selection schemes in the literature. Then, we generalize the idea of relay selection by allowing more than one relay to cooperate. The SNR-optimal multiple relay selection scheme can be achieved by exhaustive search, whose complexity increases exponentially in the network size. To reduce the complexity, several SNR-suboptimal multiple relay selection schemes are proposed, whose complexity is linear in the number of relays. They are proved to achieve full diversity. Simulation shows that they perform much better than the corresponding single relay selection methods and very close to the SNR-optimal multiple relay selection scheme. In addition, for large networks, these multiple relay selection schemes require the same amount of feedback bits from the receiver as single relay selection schemes.