Relay Placement Research Articles

RELAY DEPLOYMENT ALGORITHMS IN WIRELESS SENSOR NETWORKS: A SURVEY

Wireless Sensor Networks (WSNs) are subject to failures. Even though reliable routing protocols for WSNs exist and are well-understood, the physical network topology must ensure that alternate routes with an acceptable length to the sinksare in fact available when failures occur. This requires a sensor network deployment to be planned with an objective of ensuring some measure of robustness in the topology, so that when failures do occur the protocols can continue to offer reliable delivery. To ensure that sensor nodes have sufficient paths, it may be necessary to add a number of additional relay nodes, which do not sense, but only forward data from other nodes. In this paper, we review a range of existing algorithms to deploy relay nodes for fault tolerance. We classify the state-of-the-art relay placement algorithms based on routing structures, connectivity requirements, deployment locations, and fault-tolerant requirements.

Outage analysis for multiuser underlay cognitive TWRN with antenna selection and user scheduling

This paper investigates the outage performance of cellular two-way amplify-and-forward (AF) cooperative spectrum sharing systems in the presence of primary user (PU) network and multiple secondary user (SU) destinations. A general Nakagami-m fading environment has been used, where distinct fading parameters, as well as unequal average fading powers between the interference and relaying links, are assumed. Focusing on the cooperation process among the SU nodes and making use of the underlay cognitive approach, an approximate closed-form expression for the overall outage probability (OOP) of the secondary network is derived. In this analysis, an opportunistic scheduling and transmit antenna selection (TAS) algorithm in the secondary network has been employed. Considering the interference constraints due to the presence of PU receiver, power allocation of secondary user is done. The effects of fading severity, secondary network relay placement, the number of PU & SU transmit antenna, and number of SUs on the end-to-end system performance are examined through some representative numerical plots. Moreover, to minimize the secondary network OOP, we investigate the optimization problems of relay position. Monte Carlo simulation results are presented to corroborate the proposed analysis.

Performance Analysis of Wireless Powered DF Relay System Under Nakagami-$m$ Fading

In this paper, we analyze the average symbol error rate (SER) for a wireless powered three-node decode-and-forward (DF) relaying system in Nakagami- $m$ fading environment. $M$ -ary phase-shift keying modulated data at source is communicated to destination through energy-constrained relay node in three time slots. In the first slot, the signal transmitted by the source is used for energy harvesting at the relay node. Next two slots are employed for selective DF relaying, where relay transmits using the energy harvested from the source node. The source node is assumed to have a dedicated power supply. We analyze the end-to-end average SER expressions using the moment generating function based approach for two relaying scenarios: i) the direct link between the source and the destination exists and ii) the direct link is deeply faded and therefore can be ignored. The asymptotic approximations of the average SER are also obtained to determine the optimal energy allocated for each transmission. Since energy is related to the power transmitted at a node and the slot duration, the optimal energy expression can be judiciously used to optimize power and time for the corresponding slot. The effects of modulation order, relay placement, and channel conditions on the performance of the system with and without optimal resource allocation are investigated. The achievable diversity order and the throughput are also analyzed.

Satisfactory video dissemination on FANETs based on an enhanced UAV relay placement service

The user experience on watching videos transmitted by a flying ad hoc networks (FANETs) should always be satisfactory even under influence of topology changes in reason of the unmanned aerial vehicles (UAVs) mobility. However, one of the main challenges to route packets in FANETs is how to mitigate the effects of UAV mobility to preclude communication flaws, delays, and void area, which hence increase the packet loss over video transmissions. In this way, routing protocols require an efficient relay placement service to find out the ideal location for UAVs that act as relay nodes, and thus mitigating the effects of UAV movements on the quality of experience (QoE) of transmitted videos. In this article, we introduce a massive analysis of our proposed relay placement mechanism, called MobiFANET, in order to diagnose the impact of videos with different characteristics on the QoE and route failure. We also present detailed information about the MobiFANET mechanism, as well as the contributions of each component on the routing performance. Simulation results show how MobiFANET works jointly with a routing protocol for satisfactory multimedia transmission, where it provides better QoE and a reduction of the number of route failures compared to existing routing protocols.

Wireless relay placement optimization in underground room and pillar mines

Wireless relay placement optimization in underground room and pillar mines

An Efficient IR-HARQ Power Allocation for Relay-Aided Cellular Networks

Energy-efficient and reliable data transmission is a challenging task in wireless relay networks (WRNs). Energy efficiency in cellular networks has received significant attention because of the present need for reduced energy consumption, thereby maintaining the profitability of networks, which in turn makes these networks “greener”. The urban cell topography needs more energy to cover the total area of the cell. The base station does not cover the entire area in a given topography and adding more number of base stations is a cost prohibitive one. Energy-efficient relay placement model which calculates the maximum cell coverage is proposed in this work that covers all sectors and also an energy-efficient incremental redundancy-hybrid automatic repeat request (IR-HARQ) power allocation scheme to improve the reliability of the network by improving the overall network throughput is proposed. An IR-HARQ power allocation method maximizes the average incremental mutual information at each round, and its throughput quickly converges to the ergodic channel capacity as the number of retransmissions increases. Simulation results show that the proposed IR-HARQ power allocation achieves full channel capacity with average transmission delay and maintains good throughput under less power consumption. Also the impact of relaying performance on node distances between relay station and base station as well as between user and relay station and relay height for line of sight conditions are analyzed using full decode and forward (FDF) and partial decode and forward (PDF) relaying schemes. Compared to FDF scheme, PDF scheme provides better performance and allows more freedom in the relay placement for an increase in cell coverage.

Asynchronous Stochastic Approximation Based Learning Algorithms for As-You-Go Deployment of Wireless Relay Networks Along a Line

We are motivated by the need, in emergency situations, for impromptu (or “as-you-go”) deployment of multihop wireless networks, by human agents or robots (e.g., unmanned aerial vehicles (UAVs)); the agent moves along a line, makes wireless link quality measurements at regular intervals, and makes on-line placement decisions using these measurements. As a first step, we have formulated such deployment along a line as a sequential decision problem. In our earlier work, reported in [1] , we proposed two possible deployment approaches: (i) the pure as-you-go approach where the deployment agent can only move forward, and (ii) the explore-forward approach where the deployment agent explores a few successive steps and then selects the best relay placement location among them. The latter was shown to provide better performance (in terms of network cost, network performance, and power expenditure), but at the expense of more measurements and deployment time, which makes explore-forward impractical for quick deployment by an energy constrained agent such as a UAV. Further, since in emergency situations the terrain would be unknown, the deployment algorithm should not require a-priori knowledge of the parameters of the wireless propagation model. In [1] , we, therefore, developed learning algorithms for the explore-forward approach. The current paper fills in an important gap by providing deploy-and-learn algorithms for the pure as-you-go approach. We formulate the sequential relay deployment problem as an average cost Markov decision process (MDP), which trades off among power consumption, link outage probabilities, and the number of relay nodes in the deployed network. While the pure as-you-go deployment problem was previously formulated as a discounted cost MDP (see [1] ), the discounted cost MDP formulation was not amenable for learning algorithms that are proposed in this paper. In this paper, first we show structural results for the optimal policy corresponding to the average cost MDP, and provide new insights into the optimal policy. Next, by exploiting the special structure of the average cost optimality equation and by using the theory of asynchronous stochastic approximation (in single and two timescale), we develop two learning algorithms that asymptotically converge to the set of optimal policies as deployment progresses. Numerical results show reasonably fast speed of convergence, and hence the model-free algorithms can be useful for practical, fast deployment of emergency wireless networks.

Amplify-and-Forward Strategy Using MRC Reception Over FSO Channels with Pointing Errors

Free-space optical (FSO) systems offer ultrahigh data rates for a number of terrestrial applications. This paper presents what we believe is the first characterization of average bit error rate (BER) for a cooperative FSO system that uses channel side information-assisted amplify- and-forward (AF) relaying when line-of-sight (LOS) is available. This paper uses maximum ratio combining reception at the destination node to maximize the output signal-to-noise ratio under pointing error effects. An asymptotic closed-form expression for the BER is obtained over gamma–gamma fading channels with pointing errors. The developed asymptotic expression is used to analyze the diversity order gain in relation to the direct path link. The maximum diversity order is determined to be βSD + min(βSR, βRD), where βSD, βSR, and βRD are atmospheric turbulence parameters corresponding to the source–destination, source-relay, and relay-destination links, respectively. Moreover, optimal relay placement, which plays an important role in the performance, is derived by taking full advantage of asymptotic expressions without the need to use optimization methods. Obtained results corroborate that a higher diversity order gain and, hence, a better BER performance, is achieved compared to the direct path link and equivalent AF dual-hop transmissions.

A Pragmatic Relay Placement Approach in 3-D Space and Q-Learning-Based Transmission Scheme for Reliable Factory Automation Applications

The biggest challenge in adopting industrial wireless sensor networks (IWSNs) for factory automation applications is to provide low latency and highly reliable communication in harsh factory environments. IEEE 802.15.4e low latency deterministic network (LLDN) mode attempts to address this requirement at the medium access control (MAC) layer. However, the measures offered by this mode are inadequate considering realistic factory environments, suffering from noise, interference, multipath fading, and resulting in frequent packet losses. Cooperative diversity using relay nodes and incorporation of forward error correction (FEC) techniques are the two conventional ways to enhance communication reliability. However, the challenge lies in the placement of relay nodes considering a realistic three-dimensional (3-D) factory space and satisfying various physical, performance, and energy-related constraints. Moreover, the versatile and dynamic behavior of factory environment demand that the solutions offered to enhance communication reliability must be generic and adaptive, thereby eliminating the need for unnecessary redesigns. This paper proposes a twofold solution to enhance the communication reliability offered by 802.15.4e LLDN. First, an efficient and pragmatic relay-placement strategy based on rainbow product ranking algorithm for a 3-D factory space. Second, an adaptive transmission scheme (ATS) inspired from reinforcement learning (RL) technique called Q-learning is proposed, which incorporates cooperative diversity and Reed Solomon (RS) block codes. The effectiveness of the proposed solution is established and demonstrated using a real-world case study.

Two-tiered relay node placement for WSN-based home health monitoring system

Motivated by the needs of health monitoring at home (or a senior center) using a sensor network system, we study the problem of how to place the relay nodes so that the data collection and localization requirements of the monitoring system can be satisfied. By exploiting the inherent nature of the problem, we model it as finding a minimum connected k-dominating (k ≥ 3) set. Instead of using an idealistic disk radio model, we explicitly take into account the obstacles’ effect on the radio propagation in an indoor environment. We prove that the problem is NP-hard and propose an efficient greedy algorithm ORPA (Optimal Relay Placement Algorithm) to compute in polynomial time the best locations to place the relays. Results of extensive simulations have shown that by using our proposed algorithm ORPA, the number of relays required can be substantially reduced in comparison to the random placement and two-stage placement strategies. We also study the impact of the transmission power and the grid size on the algorithm and system performance. The result and method presented in the paper is useful to today’s indoor deployment of practical WSN-based monitoring system and to ensure network connectivity with minimal relay nodes.

Joint Optimization of Molecular Resource Allocation and Relay Positioning in Diffusive Nanonetworks

We consider a realistic two-hop diffusion-based molecular communication (DbMC) system with spherical absorbing receivers in the presence of molecular degradation and noises. We address the problem of joint optimization of molecules allocation and relay location for the given detection thresholds in order to minimize the error probability of budget limited DbMC system. Numerical and simulation results reveal the improvement in error performance when molecules distribution and relay placement are in accordance with their joint optimal value. Moreover, it is found that as the relay detection threshold increases, more molecules are needed to be allocated to the source while relay need to be placed closer to the destination in order to satisfy the optimization criteria. Eventually, we demonstrate the effectiveness of our optimization solution through 3D and contour plots illustrating the convergence time.

Joint Optimal Design for Outage Minimization in DF Relay-Assisted Underwater Acoustic Networks

This letter minimizes outage probability in a single decode-and-forward relay-assisted underwater acoustic network without direct source-to-destination link availability. Specifically, a joint global-optimal design for relay positioning and allocating power to source and relay is proposed. For analytical insights, a novel low-complexity tight approximation method is also presented. Selected numerical results validate the analysis and quantify the comparative gains achieved using optimal power allocation and relay placement strategies.

Secure Transmission in SWIPT-Powered Two-Way Untrusted Relay Networks

In this paper, we investigate the secure transmission in two-way untrusted amplify-and-forward relay networks with simultaneous wireless information and power transfer (SWIPT). Two secure SWIPT relaying strategies, namely, secure power splitting (SPS) and secure time switching (STS), are studied with the objective of secrecy rate (SR) and secure energy efficiency (SEE) maximization. First, the high signal-to-noise ratio approximations of SR and SEE are established, based on which non-convex SPS-based and convex STS-based SR maximization problems are formulated to jointly optimize the source transmit power and resource division ratio. Suboptimal solutions are obtained by employing Dinkelbach's method and Newton's method, respectively. Furthermore, to guarantee both the energy efficiency and secure quality of service (QoS) performance, SEE maximization problems are formulated with the consideration of the energy harvesting activation constraint and the target SR requirement. The intractable non-convex SEE maximization problems are reformulated as parameter programming, transformed to Lagrange dual problems, and finally solved by two SEE resource allocation algorithms with low complexity. Numerical results verify the convergence and effectiveness of the proposed algorithms and provide new insights into relaying strategy design and secure relay placement.

Power‐constrained, spectral efficiency‐optimal, green cooperative device‐to‐device communication systems

The author consider a relay-assisted, two hop, cooperative device-to-device (D2D) communication system where a source device S transmits data to a destination device D using a non-regenerative cooperative relay whose average transmit power is constrained. For the cooperative D2D system, the author consider the problem of optimally adapting the relay gain as a function of fading gains of S–R and R–D links to maximise fading-averaged spectral efficiency. The author derive the spectral efficiency-optimal relay gain adaptation policy (SERGAP), which determines optimal gain for the relay, and, analyse the fading-averaged spectral efficiency of SERGAP. To gain more insights, the author derive upper bounds on the average spectral efficiency, and, also investigate its asymptotic behaviour using an insightful analysis. Furthermore, the author extend the fading-averaged analysis to a system having multiple relays. The author also present numerical results for single relay and multiple relay systems and benchmark the proposed policy's performance with conventional and suboptimal relaying policies. The author show that SERGAP delivers higher average spectral efficiency than conventional relaying policies. Finally, spectral efficiency-optimal relay placement for the proposed policy is also investigated via simulations, and, the author find that it is different from the suboptimal relaying policies.

Optimal relay placement for lifetime maximization in wireless underground sensor networks

Because of highly lossy underground channels and the difficulty in recharging the buried sensor nodes (SNs), power conservation is a primary objective in the design of wireless underground sensor networks (WUSNs). One promising approach to prolonging the lifetimes of WUSNs is to deploy aboveground relay nodes (RNs) to relay the traffic. However, there are several challenges. First, the candidate locations of RNs are affected by the terrestrial environment. Second, signal attenuation is complex because of the multimedium propagation. Third, the optimal placement problem has to be considered in a three-dimensional space. Finally, load balancing among RNs is required to ensure that there is no overloading or exhausting of a single node. In this paper, the RN placement problem in WUSNs is modeled and formulated for the first time; the goal is to deploy a limited number of RNs to maximize the lifetimes of WUSNs under system constraints, such as locations, load balancing, network topology, and a practical channel model. Furthermore, the problem is reformulated by introducing an extra decision vector to transform the original constraints into linear constraints, and then, a two-phase method is presented to solve the problem efficiently. Extensive simulations are carried out to evaluate the performance of the proposed method.

Measurement Based As-You-Go Deployment of Two-Connected Wireless Relay Networks

Motivated by the need for impromptu or as-you-go deployment of wireless sensor networks in some situations, we study the problem of optimal sequential deployment of wireless sensors and relays along a line (e.g., a forest trail) of unknown length. Starting from the sink node (e.g., a base station), a ”deployment agent„ walks along the line, stops at equally spaced points (”potential„ relay locations), placing relays at some of these points, until he reaches a location at which the source node (i.e., the sensor) needs to be placed, the objective being to create a multihop wireless relay network between the source and the sink. The deployment agent decides whether to place a relay or not at each of the potential locations, depending upon the link quality measurements to the previously placed relays. In this article, we seek to design efficient deployment algorithms for this class of problems, to achieve the objective of 2-connectivity in the deployed network. We ensure multi-connectivity by allowing each node to communicate with more than one neighbouring node. By proposing a network cost objective that is additive over the deployed relays, we formulate the relay placement problem as a Markov decision process. We provide structural results for the optimal policy and evaluate the performance of the optimal policy via numerical exploration. Computation of such an optimal deployment policy requires a statistical model for radio propagation; we extract this model from the raw data collected via measurements in a forestlike environment. To validate the results obtained from the numerical study, we provide an experimental study of algorithms for 2-connected network deployment.

Relay Placement for Coverage Extension in Cellular Wireless Networks Under Composite Fading Model

In relay-assisted cellular networks, mobile stations are connected to base station through two or more single-hop communication links, where the intermediate nodes act as relay stations (RSs). The focus of this paper is on two-hop relay assisted cellular networks, where optimal relay placement is a crucial issue for achieving maximum extension of the cell coverage. However, the location of RS has significant impact on signal-to-interference plus noise ratio (i.e., SINR) and outage probability experienced on the access and backhaul links. Moreover, the frequency re-use factor also has significant influence on the SINR. In this paper, we develop analytical models for computing the SINR and outage probability performance of a two-hop relay assisted cellular network for both downlink (DL) as well as uplink (UL) transmission scenarios, considering the impact of path loss, shadowing, Nakagami fading and co-channel interference. We then investigate optimal placement of RS while satisfying the required criterion on probability of correct decoding, initially by considering the DL scenario alone and then by considering both DL and UL scenarios jointly. Through extensive evaluations, we report the impact of realistic propagation models on outage probability, optimal relay position and the cell coverage radius. Further, the model can be used to find the impact of co-channel re-use factor on optimal relay positioning in two-hop cellular networks.

Optimal Location of Energy Efficient DF Relay Node in $$\varvec{\kappa}$$ κ – $$\varvec{\mu }$$ μ Fading Channel

We investigate the optimal location of an adaptive decode and forward relay operating over a $$\kappa$$ – $$\mu$$ fading channel. The $$\kappa$$ – $$\mu$$ statistics provides a generalized line-of-sight propagation model which includes fading models like Rayleigh, Nakagami, Rician as special cases. We restrict our analysis to collinear relay placement, i.e. the relay node $$(R_n)$$ is on the same straight line between the source node $$(S_n)$$ and the destination node $$(D_n)$$ . In the non-cooperative mode, $$D_n$$ accepts only the two-hop transmission via $$R_n$$ and discards any direct signal that may be available from $$S_n$$ . On the other hand, in the cooperative mode, $$D_n$$ accepts both the replicas and combine them following either selection combining (SC) or maximum ratio combining (MRC). It is interesting to see that such cooperation does not always lead to energy saving, especially for small $$S_n-D_n$$ separation. Also, worth mentioning the fact that MRC may not be optimal from the energy efficiency perspective, and SC can outperform MRC under certain channel conditions. In our paper, we also studied how parameters like spectral efficiency (R), path loss exponent (n), and fading parameters ( $$\kappa ,\mu$$ ) affect the optimal relay placement location.

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

Deploy-As-You-Go Wireless Relay Placement: An Optimal Sequential Decision Approach Using the Multi-Relay Channel Model

We use information theoretic achievable rate formulas for the multi-relay channel to study the problem of as-you-go deployment of relay nodes. The achievable rate formulas are for full-duplex radios at the relays and for decode-and-forward relaying. Deployment is done along the straight line joining a source node and a sink node at an unknown distance from the source. The problem is for a deployment agent to walk from the source to the sink, deploying relays as he walks, given the knowledge of the wireless path-loss model, and given that the distance to the sink node is exponentially distributed with known mean. As a precursor to the formulation of the deploy-as-you-go problem, we apply the multi-relay channel achievable rate formula to obtain the optimal power allocation to relays placed along a line, at fixed locations. This permits us to obtain the optimal placement of a given number of nodes when the distance between the source and sink is given. Numerical work for the fixed source-sink distance case suggests that, at low attenuation, the relays are mostly clustered close to the source in order to be able to cooperate among themselves, whereas at high attenuation they are uniformly placed and work as repeaters. We also prove that the effect of path-loss can be entirely mitigated if a large enough number of relays are placed uniformly between the source and the sink. The structure of the optimal power allocation for a given placement of the nodes, then motivates us to formulate the problem of as-you-go placement of relays along a line of exponentially distributed length, and with the exponential path-loss model, so as to minimize a cost function that is additive over hops. The hop cost trades off a capacity limiting term, motivated from the optimal power allocation solution, against the cost of adding a relay node. We formulate the problem as a total cost Markov decision process, establish results for the value function, and provide insights into the placement policy and the performance of the deployed network via numerical exploration.