Multi-hop Relay Research Articles

Outage and throughput performance of a multihop network with an adaptive power splitting-based energy harvesting

ABSTRACT In this letter, throughput performance of radio frequency (RF) energy harvesting-based multihop decode forward relay network with a novel adaptive harvesting scheme is proposed and performance is investigated. In the proposed adaptive power splitting scheme, the power splitting factors are adjusted dynamically to achieve the maximum end to end signal-to-noise ratio (SNR) by equalising the SNR at all nodes. The statistics of variation of power splitting factors of each node are reported. The simulation results show that the performance of the proposed scheme outperformed in comparison with the conventional scheme in terms of throughput and outage probability.

Path selection with Nash Q‐learning for remote state estimation over multihop relay network

SummaryIn this article, the security issue of remote state estimation is investigated for multihop relay networks interrupted by an attacker launching denial‐of‐service attacks. Since the presence of the relay enriches the communication topology, there might exist several paths connecting the sensor and the estimator, consisting of the corresponding channels. Thus, it is reasonable for the sensor to select the path with a lower dropout rate to enhance the system performance measured by the estimation error, due to the dropout rate changing with the channel. However, as an adversary, the objective of the jammer is to deteriorate the corresponding performance through launching attack on the communication path selectively. For addressing the problem on the behalf of both of the sensor and the jammer, we first formulate this problem as a two‐player zero‐sum stochastic game model, and then present a Nash Q‐learning algorithm to explore the equilibrium point for both players, under the assumption that both of them are rational players. Furthermore, the existence of equilibrium point for this problem is proved analytically. Moreover, a more general case of the channel attack, under which the jammer can attack any channels among this network, is considered. Finally, numerical results are presented to verify the effectiveness of the algorithm proposed and the theorem results.

Capacity and Delay Analysis for Large Social-Aware Mobile Ad Hoc Wireless Networks

Most mobile ad hoc wireless networks have social features. It is a fundamental problem how to understand the performances of social-aware mobile ad hoc wireless networks. In this paper, we consider a wireless network area, with restricted mobility model and rank-based social model. On this basis, we investigate the upper bound of throughput capacity in such networks using the protocol interference model. By tessellating the network area into cells spatially and dividing time into slots temporally, we propose a multi-hop relay and slots allocation scheduling strategy. Then, we derive the achieved throughput capacity under this strategy. Results show per-node throughput is related to parameter of social model and range of node motion. In addition, we also study the delay varies by queueing theory in such network. Finally, we discuss capacity-delay tradeoffs in such networks. These results are beneficial to the design of network protocols in large social-aware mobile ad hoc wireless networks.

Spatial-modulated physical-layer network coding based on block Markov superposition transmission for maritime relay communications

As an alternative to satellite communications, multi-hop relay networks can be deployed for maritime long-distance communications. Distinct from terrestrial environment, marine radio signals are affected by many factors, e.g., weather conditions, evaporation ducting, and ship rocking caused by waves. To ensure the data transmission reliability, the block Markov superposition transmission (BMST) codes, which are easily configurable and have predictable performance, are applied in this study. Meanwhile, the physical-layer network coding (PNC) scheme with spatial modulation (SM) is adopted to improve the spectrum utilization. For the BMST-SM-PNC system, we propose an iterative algorithm, which utilizes the channel observations and the a priori information from BMST decoder, to compute the soft information corresponding to the XORed bits constructed by the relay node. The results indicate that the proposed scheme outperforms the convolutional coded SM-PNC over fast-fading Rician channels. Especially, the performance can be easily improved in high spatial correlation maritime channel by increasing the memory m.

On optimal relaying strategies for VANETs over double Nakagami-m fading channels

Vehicular ad hoc networks (VANETs) are able to facilitate data exchange among vehicles and provide diverse data services. The benefits of cooperative communications are such as to make it a proper idea to improve the achievable rate and diversity in VANETs. We investigate a dual-hop relay vehicular network with different transmit powers in vehicles on non-uniform shadowed double Nakagami-m fading channels in the presence of non-uniform co-channel interferers. In this paper, we investigate the diversity-multiplexing tradeoff (DMT) in such a network for three different schemes, namely, dynamic decode and forward (DDF), dynamic quantize map and forward and static quantize map and forward and prove that the DDF strategy has the optimal DMT. Also, the optimal listening and transmitting time of vehicles in various strategies as a function of the channel conditions in vehicles are determined. Finally, we extend our results to a general multi-hop relay vehicular network model with multiple half-duplex relay terminals and different average SNRs over links.

Multi-Hop Relay Selection Based on Fade Durations

In cooperative relaying, the selection of relays could be based on different parameters. The most well-known and frequently used metric is the signal-to-noise ratio (SNR). In this method of relay selection, the rapid fluctuation of the signal (i.e., fading) is not taken into account in the selection criteria. Such rapid signal change may cause significant loss of information, degrade signal quality for voice or video connections, or could make the channel coding fail. An alternative method of relay selection in a cooperative relay network is by considering fading. Such methods include average fade duration (AFD) and fade duration outage probability (FDOP), which are based on time correlation statistics. Both the AFD and the FDOP are computed in reference to a threshold value for signal quality. This work derives new formulas for two hop and three hop relay paths, with three hop paths given a penalty cost. Then optimization algorithms for each type of relay selection method are derived, including total path and link-by-link optimization. Simulation results provide optimal AFD and FDOP paths for various random network topologies. These paths are then compared to paths that would be found if SNR metrics were used instead. It is shown that SNR optimization results in much different performance. For cases of four sources and four relays, SNR based optimization frequently chose different relay paths, as low as only 63% of the same relay paths as FDOP or AFD optimizations. Because fade duration methods more accurately control the fading nature and true quality of the signals, the results here provide significant improvements in relay performance and allow two and three hop relay paths to be implemented effectively.

Energy-Aware Data Gathering Mechanism for Mobile Sink in Wireless Sensor Networks Using Particle Swarm Optimization

In order to mitigate the hot spot problem and prolong the network lifetime, data gathering with mobile sink is an effective measure to enhance the system performance. However, the movement strategy of sink node can be regarded as traveling salesman problem, which can hardly obtain the solution with polynomial running time. To address above problem, an energy-aware data gathering mechanism for mobile sink in wireless sensor networks using particle swarm optimization is introduced. Firstly, the mathematical model is established according to the total energy consumption and delay constraints for mobile sink’s data collection. Then, the optimal rendezvous points are selected to aggregate data originated from the source nodes through multi-hop relay, and the aggregation tree will be constructed for data transmission. The spanning tree is encoded into particles, and the random method is designed to generate the data collection spanning tree with constrain of tree height limit. Furthermore, a particle swarm optimization strategy with adaptive elite mutation is designed to improve the population diversity and avoid falling into the local optimal solution prematurely. Experimental results show that the proposed method can meet the delay requirements and reduce the total energy consumption of the network.

Optimizing Wireless Sensor Networks Based on Collaborative Beamforming

Abstract With the expansion of the scale of the Internet of Things, the transmission distance and speed of wireless networks need to be improved. Due to the limitation of power and energy of sensor nodes, data transmission is basically carried out by multi-hop relay. Collaborative beamforming is a technology that uses multiple sensor nodes to form a virtual antenna array to transmit high-gain and directional beams, which greatly enhances the transmission range. Compared with the muilt-hop network, collaborative beamforming can reduce the numbers of hop or even transmit data to the target node at one time, thus reducing the time required for routing and forwarding. This means that collaborative beamforming can transmit data more quickly and improve data throughput. In this paper, a brief introduction of cooperative beamforming is given. Then we propose an algorithm based on Collaborative beamforming. Simulation results show that the Collaborative beamforming wireless sensor networks can achieve better throughput compared with multi-hop networks.

Relay Probing for Millimeter Wave Multi-Hop D2D Networks

The communications in the millimeter wave (mmWave) band, e.g., WiGig (60 GHz), is considered as one of the main components of 5G and beyond 5G (B5G) networks. However, it is characterized by short range transmissions along with high susceptibility to path blockage, e.g., human shadowing. Thus, mmWave multi-hop relaying using device to device (D2D) connections turns to be an efficient solution to extend its communication range and to route around blockages. In this context, relay probing is essential to discover/explore the candidate multi-hop routes from source-to-destination and then select the best route among them. However, a trade-off exists between relay probing and the required overhead coming from mmWave beamforming training. In this paper, taking advantage of the multi-band μW /mmWave relay nodes, an efficient multi-hop relay probing scheme is proposed for mmWave D2D routing. In this scheme, the collected μW received signal strengths (RSSs) among the distributed relay nodes are used to estimate the probability of their mmWave signal-to-noise power ratios (SNRs) while considering line-of-sight (LOS) and non-LOS (NLOS) path availabilities. Then, based on a proposed probabilistic metric, a hierarchical search algorithm is proposed to jointly discover the relay nodes along the candidate multi-hop routes and enumerate the number of routes expected to maximize the spectral efficiency of the whole path from source-to-destination. This is done in an offline phase, and only the relay nodes located within the pre-selected multi-hop routes are requested to do online relay probing. Numerical analysis confirms the superiority of the proposed mmWave multi-hop relay probing scheme over the candidate techniques.

Performance Analysis of Incremental Relaying in Multi-Hop Relay Networks

Incremental relaying (IR) is shown to improve the end-to-end throughput of multi-hop relay networks. In this paper, two IR strategies under perfect and imperfect channel state information (CSI) scenarios are investigated. In each hop, relays which are able to correctly decode the message from the previous hop form a decoding set. In the first strategy named IR with best-last arbitrary-rest (IR-BLAR), one relay is arbitrarily selected from the decoding set to retransmit the message, except that in the last decoding set the relay which has the highest signal-to-noise ratio (SNR) to the destination is selected for retransmission. In the second strategy called IR with maximum decoding set (IR-MaxDS), in each decoding set one relay which has the largest number of “good” channels in the following hop is selected, except that in the last hop relay selection is the same as IR-BLAR. The performance of these strategies is analyzed in terms of end-to-end outage probability and throughput in both perfect and imperfect CSI cases. Numerical results are presented from analysis which closely match those from simulations. It is shown that by applying IR, end-to-end outage probability and throughput can be significantly improved.

Condition and location-aware channel switching scheme for multi-hop multi-band WLANs

Multi-hop relay networks are deployed to restore communication environment in the catastrophe stricken area. Deployment of these networks are fast and easy but performance remains miserably low, as a result of relay nature of the networks. Given the surge of bandwidth hungry applications, performance such as high data rates, high throughput and low latency is a concern in traditional one-hop wireless LANs as well. Performance of wireless networks is subject to the channel conditions and difference in performance of consecutive links that can result in buffer overflow or channel under-utilization. One way to cope up with deteriorating channel conditions is channel switching. However, given the limited number of orthogonal channels, the performance gain may be insignificant and ephemeral. Motivated by this fact, in this paper, we propose channel switching over multiple bands where the relevant characteristics of the bands and physical conditions are taken into the account. We develop a model that dynamically switches the channel of the link when its throughput begins to decline. The proposed model predicts exactly when will packet fail to reach the destination, hence depending upon the channel conditions and location of the node, the new channel is assigned from the band offering the best performance in terms of throughput and delay. To cope up with difference in performance on consecutive links, we propose a receiver's feedback based bitrate adaptation scheme. Simulations results show significant improvement in the throughput and delay of the network.

A REVIEW OF RELAY NETWORK ON UAVS FOR ENHANCED CONNECTIVITY

One of the best evolution in technology breakthroughs is the Unmanned Aerial Vehicle (UAV). This aerial system is able to perform the mission in an agile environment and can reach the hard areas to perform the tasks autonomously. UAVs can be used in post-disaster situations to estimate damages, to monitor and to respond to the victims. The Ground Control Station can also provide emergency messages and ad-hoc communication to the Mobile Users of the disaster-stricken community using this network. A wireless network can also extend its communication range using UAV as a relay. Major requirements from such networks are robustness, scalability, energy efficiency and reliability. In general, UAVs are easy to deploy, have Line of Sight options and are flexible in nature. However, their 3D mobility, energy constraints, and deployment environment introduce many challenges. This paper provides a discussion of basic UAV based multi-hop relay network architecture and analyses their benefits, applications, and tradeoffs. Key design considerations and challenges are investigated finding fundamental issues and potential research directions to exploit them. Finally, analytical tools and frameworks for performance optimizations are presented.

Simultaneous Wireless Information and Power Transfer for Decode-and-Forward Multihop Relay Systems in Energy-Constrained IoT Networks

This paper studies a multi-hop decode-and-forward (DF) simultaneous wireless information and power transfer (SWIPT) system where a source sends data to a destination with the aid of multi-hop relays which do not depend on an external energy source. To this end, we apply power splitting (PS) based SWIPT relaying protocol so that the relays can harvest energy from the received signals from the previous hop to reliably forward the information of the source to the destination. We aim to solve two optimization problems relevant to our system model. First, we minimize the transmit power at the source under the individual quality-of-service (QoS) threshold constraints of the relays and the destination nodes by optimizing PS ratios at the relays. The second is to maximize the minimum system achievable rate by optimizing the PS ratio at each relay. Based on convex optimization techniques, the globally optimal PS ratio solution is obtained in closed-form for both problems. By setting the QoS threshold constraint the same for each node for the source transmit power problem, we discovered that either the minimum source transmit power or the maximum system throughput can be found using the same approach. Numerical results demonstrate the superiority of the proposed optimal SWIPT PS design over conventional fixed PS ratio schemes.

Efficient strategies to reduce power consumption in MANETs.

In current circumstances, where amelioration in technology is elevating, power optimization is of grave concern, whilst perceiving portable conditions. The focus is to design an efficient system with an aim to reduce power consumption and improve performance of other metrics. Heterogeneous wireless systems will command in the next-generation wireless networks with the aggregation of different remote access mechanisms. A node in MANET (Mobile Adhoc NETworks) while consuming significant amount of energy practices data transmission and data retrieval process whilst bonding with other neighboring nodes that are within its range. The proposed work implements User Specified energy model and DYMO (DYnamic Manet On-demand) routing protocol. Further, additional features of IEEE 802.11 i.e., Power Saving Mode is employed. To obtain enhanced coverage at targeted areas, multi-hop relay strategy is taken into account, also to achieve a less power consuming network with a greater service life. Consequently, the efficiency of the devices is monitored by opting Residual Life Accurate battery model, by using different datasets of Duracell AA and AAA batteries. Simultaneously, battery model, energy model and DYMO (DYnamic Manet On-demand) are applied for IEEE 802.16 to get a comparative assessment of power consumption between IEEE 802.11 and IEEE 802.16. Results are generated for both the architectures i.e., 802.11 and 802.16 for metrics such as residual amount of energy for varying simulation time for all the nodes and for energy consumption in AODV (Ad Hoc On-Demand Distance Vector) and DYMO (DYnamic Manet On-demand) routing protocol using Qualnet version 7.4.

Deep-Reinforcement-Learning-Based Distributed Vehicle Position Controls for Coverage Expansion in mmWave V2X

In millimeter wave (mmWave) vehicular communications, multi-hop relay disconnection by line-of-sight (LOS) blockage is a critical problem, especially in the early diffusion phase of mmWave-available vehicles, where not all the vehicles have mmWave communication devices. This paper proposes a distributed position control method for autonomous vehicles to make long relays connecting to road side units (RSUs) by avoiding blockages to communicate with each other via LOS paths. Even though vehicles with the proposed method do not use the whole information of the environments and cooperate with each other, they can decide their action (e.g., lane change and overtaking) to form long relays using only information of its surroundings (e.g., surrounding vehicle positions). The decision-making problem is formulated as a Markov decision process so that autonomous vehicles can learn a practical movement strategy of making long relays by a reinforcement learning (RL) algorithm. This paper designs a learning algorithm based on a sophisticated deep reinforcement learning algorithm, asynchronous advantage actor-critic (A3C), which enables vehicles to learn a complex movement strategy quickly by its deepneural-network architecture and multi-agent-learning mechanism. Once the strategy is well trained, vehicles can distributedly move to positions where the long relay to the RSU is established. Simulations results confirm that the proposed method can increase the relay length and coverage even if the traffic conditions and penetration ratio of mmWave communication devices in learning and operation phases are different.

Cognitive Multi-Hop Multi-Branch Relaying: Spectrum Leasing and Optimal Power Allocation

In this paper, for an overlay cognitive radio network in which the primary user’s transmission is assisted by a cognitive multi-hop multi-branch network, we propose and analyze a spectrum leasing scheme that achieves full diversity in both the primary and secondary networks. Among the available branches, the best one is selected to establish a multi-hop relay link between the primary users. In return, the secondary users of the selected branch are rewarded with a fraction of spectrum to transmit their own signals over a nonorthogonal multiple-access channel. We jointly optimize the branch selection and the spectrum allocation such that the sum-rate of the secondary users is maximized under the constraint that a minimum quality-of-service (QoS) requirement in terms of the achievable rate is satisfied in the primary network. We also optimize the power allocation to the secondary users such that the asymptotic outage probability of the primary network is minimized. The analytical results show that this spectrum leasing scheme guarantees the full diversity of order $M$ in both the primary and secondary networks, where $M$ is the number of cognitive branches. The simulation results also show that optimizing the allocation of power significantly decreases the risk of spectrum leasing failure.

Interference Avoidance Position Planning in Dual-Hop and Multi-Hop UAV Relay Networks

We consider unmanned aerial vehicle (UAV)-assisted wireless communication employing UAVs as relay nodes to increase the throughput between a pair of transmitter and receiver. We focus on developing effective methods to position the UAV(s) in the sky in the presence of interference in the environment, the existence of which makes the problem non-trivial and our methodology different from the current art. We study the optimal position planning, which aims to maximize the (average) signal-to-interference-ratio (SIR) of the system, in the presence of: i) one major source of interference, ii) stochastic interference. For each scenario, we first consider utilizing a single UAV in the dual-hop relay mode and determine its optimal position. Afterward, multiple UAVs in the multi-hop relay mode are considered, for which we investigate two novel problems concerned with determining the optimal number of required UAVs and developing an optimal fully distributed position alignment method. Subsequently, we propose a cost-effective method that simultaneously minimizes the number of UAVs and determines their optimal positions to guarantee a certain (average) SIR of the system. Alternatively, for a given number of UAVs, we develop a fully distributed placement algorithm along with its performance guarantee. Numerical simulations are provided to evaluate the performance of our proposed methods.

A New Cooperative Dual-Level Game Approach for Operator-Controlled Multihop D2D Communications

With the development of wireless communications and the intellectualization of mobile devices, device-to-device (D2D) communications are considered as a standard part of future 5G networks. This new paradigm can provide better user experiences while improving the system performance such as network throughput, latency, fairness, and energy efficiency. In this study, we investigate a new dual-level D2D communication scheme consisting of multiple D2D operators and a group of mobile devices. To model the interaction among D2D operators and devices, we adopt two cooperative game approaches based on the incentive mechanism design and r-egalitarian Shapley value. At the upper level, routing paths and incentive payments for multihop relay services are decided using the incentive mechanism. At the lower level, mobile devices share the given incentive based on the r-egalitarian Shapley value. Both level control procedures are mutually dependent on each other by the proper coordination and collaboration. According to the main features of two cooperative game models, the proposed scheme takes various benefits in a fair-efficient way. Through the derived simulation results, we can verify the superiority of our proposed scheme comparing to the existing protocols. Finally, we propose further challenges and future opportunities in the research area of operator-controlled multihop D2D communications.

Cooperative secrecy transmission in multi‐hop relay networks with interference alignment

In this study, the authors consider the secrecy communication of one source-destination pair in a wireless multi-hop relay network, where each node is equipped with multiple antennas. They use the method of interference alignment for secrecy transmission in the presence of an eavesdropper. Firstly, they propose a decode-and-forward (DF) relaying protocol and give a new result on the joint probability density function of the first, second, horizontal ellipsis , kth ($k=1, 2,\ldots $k=1,2, horizontal ellipsis ) largest eigenvalues of the complex Wishart matrices $\boldsymbol{H} \boldsymbol{H}H$HHH, where $\boldsymbol{H}$H is an matrix whose elements are independent identically distributed complex Gaussian variables with zero mean and unit variance. They then utilise this result to characterise the legitimate outage probability and the diversity order of the proposed DF protocol. The case where the relay works in the amplify-and-forward (AF) mode is considered at last, and the diversity order of the proposed AF protocol is given.

Delay constrained throughput optimization in multi-hop AF relay networks, using limited quantized CSI

In this paper, we analyze the throughput of multi-hop amplify and forward (AF) relay networks in delay-constrained scenario. Using quantized channel state information (CSI), the transmission rates and powers are discretely adapted with individual average power constraint on each node. A sub-gradient projection-based algorithm is utilized, by which there is no need for probability density functions (PDFs) to solve the optimization problem. Our numerical evaluations show that the sub-gradient projection-based algorithm results in a comparable performance with an analytical approach using PDFs. As shown, a considerably better performance obtained by the designed scheme compared to previous schemes with constant power transmission. More than 70% throughput improvement is achieved by our scheme compared to constant power transmission with just two more feedback bits and a short training time required at the beginning of the transmission.