Relay Allocation Research Articles

A Secure Cooperative Image Super-Resolution Transmission with Decode-and-Forward Relaying over Rayleigh Fading Channels

In addition to susceptibility to performance degradation due to hardware malfunctions and environmental influences, wireless image transmission poses risks of information exposure to eavesdroppers. This paper delves into the image communications within wireless relay networks (WRNs) and proposes a secure cooperative relaying (SCR) protocol over Rayleigh fading channels. In this protocol, a source node (referred to as Alice) transmits superior-resolution (SR) images to a destination node (referred to as Bob) with the assistance of a mediating node (referred to as Relay) operating in decode-and-forward mode, all while contending with the presence of an eavesdropper (referred to as Eve). In order to conserve transmission bandwidth, Alice firstly reduces the size of the original SR images before transmitting them to Relay and Bob. Subsequently, random linear network coding (RLNC) is employed by both Alice and Relay on the downscaled poor-resolution (PR) images to obscure the original images from Eve, thereby bolstering the security of the image communications. Simulation results demonstrate that the proposed SCR protocol surpasses both secure relaying transmission without a direct link and secure direct transmission without relaying links. Additionally, a slight reduction in image quality can be achieved by increasing the scaling factor for saving transmission bandwidth. Furthermore, the results highlight the SCR protocol’s superior effectiveness at Bob’s end when compared to Eve’s, which is due to Eve’s lack of access to the RLNC coefficient matrices and reference images utilised by Alice and Relay in the RLNC process. Finally, the evaluation of reference images, relay allocations and diversity reception over Rayleigh fading channels confirms the effectiveness of the SCR protocol for secure image communications in the WRNs.

Outdoor Air Quality Monitoring with Enhanced Lifetime-enhancing Cooperative Data Gathering and Relaying Algorithm (E-LCDGRA) Based Sensor Network

The air continues to be an extremely substantial part of survival on earth. Air pollution poses a critical risk to humans and the environment. Using sensor-based structures, we can get air pollutant data in real-time. However, the sensors rely upon limited-battery sources that are immaterial to be alternated repeatedly amid extensive broadcast costs associated with real-time applications like air quality monitoring. Consequently, air quality sensor-based monitoring structures are lifetime-constrained and prone to the untimely loss of connectivity. Effective energy administration measures must therefore be implemented to handle the outlay of power dissipation. In this study, the authors propose outdoor air quality monitoring using a sensor network with an enhanced lifetime-enhancing cooperative data gathering and relaying algorithm (E-LCDGRA). LCDGRA is a cluster-based cooperative event-driven routing scheme with dedicated relay allocation mechanisms that tackle the problems of event-driven clustered WSNs with immobile gateways. The adapted variant, named E-LCDGRA, enhances the LCDGRA algorithm by incorporating a non-beaconaided CSMA layer-2 un-slotted protocol with a back-off mechanism. The performance of the proposed E-LCDGRA is examined with other classical gathering schemes, including IEESEP and CERP, in terms of average lifetime, energy consumption, and delay

Improving MIMO relay compressed sensing-based channel estimation and pilot allocation

Increasing the data rate of communication systems together with the performance are main goals of the communication networks in the future. Multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) relay networks as a key technology is one the main techniques to maintain the performance and data rate. Being influenced by fading channels, the MIMO-OFDM relay networks need some reliable approaches to estimate the channel response. Compressed sensing (CS) is one of the critical approaches to maintain the accuracy together with the spectral efficiency. In this paper, we have utilized CS-based approaches to estimate the MIMO-OFDM relay channel. Specifically, forward backward prediction (FBP) is used to estimate the fading channels. This approach benefits from backward correction which distinguishes it from other iterative approaches and helps interestingly in channel estimation accuracy. Moreover, in order to improve the channel estimation, pilot allocation approaches are proposed based on the system model and probability function. Furthermore, a cross entropy-based approach is utilized to propose two different approaches called sequential cross entropy self-coherence (SCE-SC) and parallel cross entropy self-coherence. Actually, mutual coherence is divided into two parts namely cross coherence and self coherence. It is demonstrated that in FBP-based approach self-coherence is important in mutual coherence. Consequently, the computations are interestingly decreased. The superiority of the method is represented using comparing simulations with other well-known approaches.

User-relay assisted cellular networks with multiple antennas

ABSTRACTUser-relay assisted OFDMA-based cellular networks have gained great importance recently since these networks are indicated as one of the powerful technologies that will contribute the 5G standard. These networks can be used with novel three-phase frame structure unlike classical two-phase frame structure and can be enhanced with multiple antennas to utilise the advantages of them. The main advantage of the three-phase frame structure is taking care of the limitations of the current transceiver design in practical systems and not allowing users to be relay and user simultaneously. Diversity and capacity gains are also the advantages of extending the network with multiple antennas. In this paper, we will use the novel three-phase frame structure for downlink MISO-OFDMA cellular networks and develop resource management algorithms as relay selection and resource allocation to observe the benefits of this system.

Relay Selection for Multi-Channel Cooperative Multicast: Lexicographic Max–Min Optimization

Cooperative multicast has been demonstrated to achieve significant performance gain over the classic source–destination transmission paradigm by exploiting spatial diversity through the participation of multiple relay nodes. As a major technical challenge, the selection of relays for a multicast session has significant impact on the multicast performance. The challenge is even more pronounced when the number of channels is limited as the relay selection is in this context coupled with channel allocation. The goal of this paper is to design a fair multicast relay selection scheme with limited channel resources. Specifically, we establish an analytical framework for this joint relay selection and channel allocation problem and develop a lexicographic max–min multicast relay selection scheme. Our design consists of two technical steps. First, we consider the maximization of the minimal data rate. By decoupling relay selection and channel allocation, the problem is transformed to a max–min–max problem, which is difficult to solve. To make this problem tractable, we reformulate it as a convex optimization problem via relaxation and smoothing, and prove the asymptotic equivalence from a geometrical perspective. Second, we propose an adjustment algorithm based on the initial max–min solution, and prove that the proposed scheme achieves lexicographic optimality. Finally, our proposed algorithm is evaluated by simulation to show its superiority over the conventional schemes.

Relay Selection and Resource Assignment for Cooperative SC-FDMA Networks

In this article, we study relay selection and resource allocation in a cooperative network that employs Single Carrier - Frequency Division Multiple Access (SC-FDMA) in the uplink direction such as in Long Term Evolution - Advanced (LTE-A) system. With SC-FDMA, the frequency resources assigned to a transmitter should be adjacent to each other in the frequency domain (adjacency constraint). We formulate the total data rate maximization problem as a non-linear combinatorial optimization problem. Through algebraic manipulations, we managed to convert the original problem in a Mixed Integer Linear Problem (MILP) that can be optimally solved by standard computational solvers. So as to reduce the computational complexity, we propose a low-complexity suboptimal solution to this problem. Additionally, we propose a transmit power adjustment in order to reduce the power consumption in the system and improve Energy Efficiency (EE) by exploiting the characteristics of the forwarding mechanism in the relays. Finally, we present simulation results so as to evaluate the performance of the proposed solutions and obtain insights on the effect of the main variables presented in the system model.

An iterated metaheuristic for the directed network design problem with relays

We study the directed network design problem with relays (DNDR), which arises in telecommunications and distribution systems where relay points are necessary. Given a directed network and a set of commodities, the DNDR consists of introducing a subset of arcs and locating relays on a subset of nodes such that in the resulting network, the total cost (arc cost plus relay cost) is minimized, and there exists a path linking the origin and destination of each commodity, in which the distances between the origin and the first relay, any two consecutive relays, and the last relay and the destination do not exceed a predefined distance limit.Since the DNDR is an NP-hard problem, we present an iterated metaheuristic based on tabu search, which iteratively solves the DNDR within two steps: generating paths for commodities, and determining optimal relay assignment associated with these paths. A cycle-based neighborhood is designed to generate neighboring solutions by replacing subpaths in commodities’ paths with new ones. Given one subpath, the new substituting subpath is found by solving a shortest path problem between its two endpoints, explicitly taking into account the impact of opening one subpath on the objective value. For each neighboring solution, the associated relay allocation is determined by exactly determined. With a set of benchmark instances and newly generated instances, we compare our approach with other available algorithms. Computational results demonstrate that our proposed algorithm is an efficient method for the DNDR.

A variable neighborhood search for the network design problem with relays

Given a set of commodities to be routed over a network, the network design problem with relays involves selecting a route for each commodity and determining the location of relays where the commodities must be reprocessed at certain distance intervals. We propose a hybrid approach based on variable neighborhood search. The variable neighborhood algorithm searches for the route for each commodity and the optimal relay locations for a given set of routes are determined by an implicit enumeration algorithm. We show that dynamic programming can be used to determine the optimal relay locations for a single commodity. Dynamic programming is embedded into the implicit enumeration algorithm to solve the relay location problem optimally for multiple commodities. The special structure of the problem is leveraged for computational efficiency. In the variable neighborhood search algorithm, the routes of the current solution are perturbed and reconstructed to generate neighbor solutions using random and greedy construction heuristics. Computational experiments on three sets of problems (80 instances) show that the variable neighborhood search algorithm with optimal relay allocations outperforms all existing algorithms in the literature.

Auction-based resource allocation for cooperative cognitive radio networks

Cooperative cognitive radio network (CCRN) is a promising paradigm to increase spectrum utilization and exploit spatial diversity. The allocation of two coupled resources, i.e. spectrum and secondary relay nodes, plays a fundamental role in the performance of CCRNs. However, previous studies either lack of incentives for both primary users (PUs) and relay nodes to participate in or consider spectrum auction and relay auction separately. In this paper, we consider a static cooperative cognitive radio network scenario with several PUs and multiple secondary user coteries, each of which consists of a set of secondary users who are interested in sharing the same secondary relay node. We model the problem of joint spectrum allocation and relay allocation as a hierarchical auction and propose two auction schemes, i.e. TERA and UERA. TERA is the first Truthful auction mechanism for Efficient Resource Allocation in CCRNs which satisfies critical economic properties. UERA is an approximate truthful scheme which adopts a uniform price for fairness in the same secondary user coteries. Furthermore, we theoretically prove TERA and UERA can achieve near-optimal revenue. Finally, extensive simulation results show that TERA and UERA are efficient and able to improve the utility of PUs and relay nodes significantly.

Low-Latency Multi-Flow Cooperative Broadcast in Fading Wireless Networks

Though a cooperative broadcast scheme has been proposed for fading environments, it has two defects: First, it only handles a packet flow from a single source node in the network, but does not consider the scenario of multiple packet flows simultaneously broadcasted from different source nodes. Second, it only allows a single relay node to forward a packet in each time slot, though multiple relay nodes forwarding in a time slot can significantly reduce broadcast latency. In this paper, we aim achieve low-latency multi-flow broadcast in wireless multi-hop networks with fading channels. To describe the interference among the transmission in different flows, we incorporate the Rayleigh fading model to the signal to noise ratio (SNR) model. Then, we introduce a cooperative diversity scheme which allows multiple relays forwarding in a time slot to reduce broadcast latency. We then formulate an interesting problem: In a fading environment, what is the optimal relay allocation schedule to minimize the broadcast latency? We propose a warm up heuristic algorithm for single-flow cooperative broadcast, based on which, we further propose a heuristic algorithm for multi-flow cooperative broadcast. Simulation results demonstrate that the two algorithms achieve lower broadcast latency than a previous method.

Collision resolving relay selection in large-scale blind relay networks

Optimal relay selection in large-scale networks is a difficult task since the network is usually considered as blind due to the high volume and collection difficulty of the relays' information. In this paper, we develop a collision resolving relay selection (CReS) scheme that achieves the optimal relay from a random set of candidates without the previous knowledge of any individual relay. By introducing stochastic geometry based quality-of-service region, the relation between the distribution of the available relay number and the transmission request is established. Furthermore, the selection phase of the CReS scheme is divided into two sub-phases according to different distributions of the relay number in boundless and bounded regions. A switch rule is proposed when several relays collide in the first sub-phase, followed by the second sub-phase to resolve the collision with the splitting algorithm. The optimal solution that requires minimum selection slots for all sub-phases is derived. In addition, a sub-optimal solution is also explored to reduce the computational complexity. The scheme shows a better applicability than conventional information-based schemes in view of its little information requirement when dealing with large-scale relay allocation problems.

Optimal user‐centric relay assisted device‐to‐device communications: an auction approach

Device-to-device (D2D) communication has recently attracted much research attention because of its potential to increase the capacity of cellular networks. Most existing works aim to maximise the overall system throughput (system-centric), which ignores the actual traffic demands of D2D users. In this study, the authors consider user-centric relay assisted D2D communications where D2D users have different evaluations for the significance of every unit of increased data rate. By considering the traffic demands of D2D users, the authors propose a Vickrey–Clarke–Groves auction based relay allocation mechanism (ARM) in which every D2D user submits a bid to the basestation (BS). The submitted bids indicate D2D users’ valuation on every unit of the increased data rate. The BS then allocates relays to D2D users by maximising the social welfare of D2D users while maintaining a predefined data rate requirement for cellular users. A payment scheme to charge D2D users for using relays is designed, and the authors show that the auction is truthful. The authors also extend the results to a general case and provide a general ARM accordingly. Extensive simulation results are provided to demonstrate the performance of the proposed mechanisms.

Energy-Efficient Relay Selection and Resource Allocation in Nonregenerative Relay OFDMA Systems

Discrete modulation in multiuser nonregenerative relay systems is less investigated in current resource allocation but is more commonly used in practical systems. In this paper, based on a set of discrete modulation levels, we formulate a joint optimization of relay selection and resource allocation under rate requirements to minimize the system transmitting power consumption and to improve energy efficiency. Since the problem cannot be easily solved due to its NP-hardness, we decompose it into two subproblems, namely, a simple relay selection method and a resource allocation method, and we develop a heuristic algorithm to find suboptimal solutions. The two-step solutions are based on power saving and virtual direct transmission, and they can reduce the dimensionality and can simplify the resource allocation of the relay networks. In addition, the power constraints at the relay stations (RSs) are considered in a way that the subcarriers on overloaded RSs are adjusted according to the joint optimization. Our results show that a satisfactory suboptimal solution close to the optimal one could be achieved, and the power constraints at RSs may have a significant impact on the total power consumption.

Relay selection for peer-to-peer cooperative OFDMA with channel distribution uncertainty

Peer-to-peer relay technique provides the opportunity of cooperative communication between users to achieve the transmission diversity. In this paper, the problem of relay selection and subcarrier allocation in peer-to-peer cooperative OFDMA system with channel distribution uncertainty is studied. The quality of service (QoS) requirements are characterized with the probabilistic constraints. The Kullback-Leibler (KL) divergence is adopted to describe the uncertainty of the channel state information (CSI), which follows a distribution deviated within a certain distance from the reference distribution. Since the probabilistic constraint is intractable, we resort to a tractable upper bound instead. The problem is solved by the interior point cutting plane (IPCP) method, which proceeds in round whereby an iterative method is designed to combine both golden section method and interior point method to find the saddle point of the constraint. Simulation results show the effectiveness of our algorithm.

Stochastic optimization in cooperative relay networks for revenue maximization

In cellular networks, cooperative relaying is an economic and promising way to enlarge the network capacity and coverage. In the case that multiple users and multiple relays are taken into account, efficient resource allocation is important in such networks. In this paper, we consider the joint relay power control with amplify-and-forward (AF) strategy and dynamic pricing for uplink cellular networks in order to maximize the network administrator’s system revenue. The system revenue is associated with pricing strategies and mobile users’ random data request, which is supported by the relay assisted transmission. To deal with the problem of the coupling in pricing and relay resource allocation, we utilize Lyapunov optimization techniques to design online pricing and relay power control without any statistic information of random events in networks. Theoretical analysis shows that the proposed algorithm can achieve a near-optimal performance and simulation results also validate its effectiveness and robustness.

Joint resource allocation and relay selection via genetic algorithm in multi‐user decode‐and‐forward cooperative systems

This study presents a joint consideration of the relay subset selection, bandwidth allocation and power distribution in multi-user decode-and-forward cooperative networks. The upper bound for the optimisation problem considered is first determined by ignoring some constraints. Thereafter, a genetic algorithm (GA) is addressed to resolve the mixed-integer non-linear programming problem involved. To accommodate this joint consideration, each chromosome in the proposed GA is divided into an integer string for relay selection, and two real number strings for bandwidth allocation and power distribution. In addition, new crossover and mutation operations are employed for this new type of chromosomes. To alleviate the complexity overhead, a low-complexity two-stage implementation is also addressed. Conducted simulations show that both of the proposed GA and the two-stage implementation can attain close performance as the upper bound and outperform some representative previous works. The two-stage implementation is in particular appealing by exhibiting negligible performance degradation with reduced computations.

Trade-off optimization for scalable video coding streaming in relay-based OFDMA networks

To achieve an optimal trade-off between video quality and energy efficiency in the uplink streaming of multi-user Scalable Video Coding (SVC) videos in relay-based Orthogonal Frequency Division Multiple Access (OFDMA) cellular networks, a cross-layer design framework that jointly selects the Transmission Policy (TP) for SVC video frames, assigns OFDMA subcarriers, and allocates power for each subcarrier is proposed. We apply the dual decomposition method to the problem, and obtain a TP selection subproblem for each SVC video adaptation and a resource allocation subproblem of Joint Subcarrier, Relay and Power Allocation (JSRPA). A second level of dual decomposition is used to divide the JSRPA problem into independent subcarrier subproblems. The proposed Cross-layer Trade-off Optimization (CTO) algorithm is sub-distributed with significantly low complexity. A performance evaluation with typical SVC video traces demonstrates that the proposed algorithm is able to converge and efficiently achieve the optimal trade-off between the video quality and energy consumption at the MSs for uplink SVC streaming.

Comments on `Fair and Efficient Relay Selection and Spectrum Allocation for Multi-User and Multi-Relay Cooperative Cellular Networks'

In a recent letter, Zhang et al. proposed a relay selection and spectrum allocation scheme in the multi-user and multi-relay cooperative cellular networks. This comment points out one inaccurate equation and the erroneous figures for the above letter. Meanwhile, the correct equation and figures are provided.

Optimal relay allocation strategy based on maximum rate in two-user multi-relay system

Cooperative communication can enhance the performance of wireless networks via relays, and so how to allocate the relay to obtain the optimal performance of system is a key issue. In this article, we consider a cooperative system where two users communicate with the destination via relays, and these relays connect with the destination by cable. Through the theoretical derivation and analysis, we obtain the optimal relay allocation strategy based on the maximum rate under the condition of relays setting forwarding thresholds. The result shows that the system has the maximum transmission rate when the relays are allocated equivalently between users. Moreover, compared with the single-user system, the results prove that diversity gain has a decisive effect on the performance in low SNR. However, with the SNR increasing, the impact of diversity gain on system rate will be reduced. In high SNR, spatial freedom degree of the channel of multiple users is brought to enhance the performance instead of diversity gain. Numerical results demonstrate the validity of the allocation strategy and conclusion arrived in this study, but we do not find the similar arguments in the literature so far, for comparison with the conclusion of this study.

A novel scheduling framework for QoS-aware OFDMA resource allocation in a network with small relay cells and macro users

Relaying is a convenient way to provide full coverage in cellular networks. In particular, small relay cells can be used as a cost-effective solution for indoor coverage in MIMO–OFDM systems. The small relay cells would need to cater for indoor users’ quality of service (QoS) expectations. One key QoS objective is delivering stable data rates for multimedia applications, which we refer to as guaranteed data rates. In this article, we consider optimization for delivering guaranteed data rates in a network with multiple relays and a macro base station, in a scenario when there are both macro users and relay users to be served. A novel scheme called cell-guaranteed bit rate by relay scheduling is proposed, with both optimal and heuristic scheduling methods. To perform the optimization we exploit resource block allocation, and parameters such as relaying duration and relay bandwidth allocation. Interference between relays and macro is avoided through time domain orthogonalization. Another key aspect of the scheme is inter-frame scheduling, wherein relay feeder links can be flexibly scheduled in any time slot along with macro users. Performance evaluation is presented using real-time indoor measurement channels and a sample test scenario. Results show the heuristic method can improve performance by 89.47% as compared to round-robin scheduling at relays and is within a 5% gap to optimal scheduling.