Multi-hop Relay Research Articles

M-ary Distributed Decision Fusion for Multihop Relay Wireless Sensor Networks: Decision Fusion Rule, Implementation Framework, and Performance Analysis

M-ary Distributed Decision Fusion for Multihop Relay Wireless Sensor Networks: Decision Fusion Rule, Implementation Framework, and Performance Analysis

MULTI-HOP RELAY SELECTION FOR COOPERATIVE SENSING IN COGNITIVE RADIO NETWORKS

Spectrum sensing is one of the essential blocks of the cognitive radio (CR) system. Cooperative spectrum sensing (CSS) enhances sensing performance by exchanging information among secondary users (SUs). The paper addresses a situation where some SUs cannot communicate their local information with the fusion center (FC) due to real-time circumstances, i.e., shadowing, large distances, increased signal interference, etc. The issue can be resolved by introducing relay nodes to assist such SUs in transmitting local information to the corresponding destination (FC), making relay selection an essential component on which the system's performance depends. This paper proposes a critical path method (CPM) based multi-hop relay selection technique to select a set of relay nodes combined to form a relay with minimum path loss. The performance of the proposed scheme is compared with that of the existing methodologies to demonstrate its robustness and efficiency in terms of end-to-end path loss and reliability. In addition, a closed-form expression of outage probability is also developed to withstand the results.

UAV-Enabled Secure Communications via Collaborative Beamforming With Imperfect Eavesdropper Information

Unmanned aerial vehicles (UAVs) are playing a pivotal role in wireless networks due to their high mobility and on-demand deployment advantages. However, the UAV-enabled communications are susceptible to be wiretapped by eavesdroppers due to the strong line-of-sight (LoS) dominated air-ground channel. In this paper, we consider a UAV-enabled secure communication scenario, in which a group of UAVs form a UAV-enabled virtual antenna array (UVAA) to transmit information towards the remote base stations (BSs) via collaborative beamforming (CB), while multiple known and unknown eavesdroppers aiming to wiretap the information. Specifically, a secure communication multi-objective optimization problem (SCMOP) is formulated to achieve the maximization of the worst-case secrecy rate, the minimization of the maximum sidelobe level (SLL) as well as the minimization of the flight energy consumption of UAVs by obtaining optimal locations and excitation current weights concerning the UAVs as well as determining an optimal receiver BS that can achieve superior communication performance. To solve the formulated SCMOP which is demonstrated to be non-convex and NP-hard, an improved multi-objective salp swarm algorithm (IMSSA) with several specific operating factors is proposed. Simulations results demonstrate that the proposed IMSSA can deal with the formulated SCMOP effectively and outperforms other benchmark strategies. Moreover, the multi-hop relay is introduced to verify the reasonability of the UVAA system, and two benchmark schemes of the formulated SCMOP are introduced to demonstrate the necessity of the formulated SCMOP. In addition, the performance of the UVAA system under certain unexpected circumstances is estimated. Finally, experimental implementation is conducted by using a Raspberry Pi and the results demonstrate the practicality of the proposed CB-based secure communication approach in real-world scenarios.

An Emergency Message Routing Protocol for Improved Congestion Management in Hybrid RF/VLC VANETs

Unexpected traffic incidents cause safety concerns and intense traffic congestion on crowded urban road networks. Vehicular ad-hoc network (VANET)-aided Intelligent Transport Systems (ITS) aim to mitigate these risks through timely dissemination of alert messages. However, conventional Radio frequency (RF) mobile ad-hoc routing protocols are ill-suited for dynamic VANET environments due to high mutual interference, packet collisions, high end-to-end delay from frequent route discoveries, and periodic beaconing requirements. Fortunately, the quickly emerging Visible Light Communications (VLC) provide complementary short-range connectivity with high bandwidth and low interference. This paper proposes an efficient adaptive routing protocol for emergency messages in dense VANET scenarios leveraging a hybrid RF/VLC system. When an incident or congestion happens, the source vehicle disseminates the information to the incoming vehicles as quickly as possible using a combination of VLC and RF communication networks. Multi-hop relays extend the connectivity if the direct links are blocked. The coverage area is partitioned into zones based on road segments, intersections, and traffic flows. The Road Side Units (RSU)s are intelligently assigned to zones and they analyze the historical traffic data to characterize each zone and decide a response strategy. We also propose a congestion detection scheme that utilizes traffic simulations to forecast the clearance times under different response strategies. The highest-scoring strategy is selected based on the predicted impacts on travel time, emissions, and driver stress levels. The proposed algorithm adaptively uses the selected strategy to proactively alleviate the predicted congestion through optimized routing and control. Overall, the protocol maximizes safety and efficiency during emergencies by leveraging the hybrid RF/VLC, incorporating real-time congestion forecasting and dynamic rerouting into the response strategies.

Outage Probability Analysis of Multi-hop Relay Aided IoT Networks

This study delves into Internet of Things (IoT) networks wherein a transmitting source communicates information to a designated recipient. The presence of signal attenuation challenges the direct transmission of information from the source to the recipient. To surmount this obstacle, we investigate IoT network communication facilitated by multi-hop relays, whereby multiple relays collaboratively enable the conveyance of data from the source to the recipient across intermediate stages. For the considered IoT networks augmented by multi-hop relays, we assess the performance of the system by analyzing the probability of transmission outage. This analysis entails the derivation of an analytical expression for evaluating the occurrence of IoT network outage. Additionally, we gauge the system's effectiveness by examining the attainable transmission rate, wherein an analytical expression is furnished to assess the IoT data rate. The empirical results, along with the analytical findings, are subsequently presented to validate the formulated expressions in the context of IoT networks empowered by multi-hop relays. Notably, the utilization of multi-hop relaying emerges as a efficacious strategy for substantially expanding the coverage scope of IoT networks.

SyRoC: Symbiotic robotics for QoS-aware heterogeneous applications in IoT-edge-cloud computing paradigm

Smart Robots, as an advanced domain of widespread concern, can be applied in diverse fields to perform compute-intensive Internet of Things (IoT) applications. However, their onboard resource constraints necessitate using the computation offloading technique to extend their capabilities. Additionally, the distributed locations of robots and the diversified quality of service (QoS) requirements of different applications pose challenges to the existing offloading works. To address these concerns, we put forward a collaborative offloading scheme for QoS-aware utility optimization for multi-robot system, and the optimization problem is formulated based on multi-attribute utility theory. Our methodology consists of three critical components: (1) we construct a symbiotic collaboration model that leverages the advantages of multiple computation modes across IoT-edge-cloud infrastructure and tap the potential of multi-hop relay transmission technology to enable efficient collaborative offloading; (2) we develop a QoS-aware preference assessment framework based on analytic hierarchy process to effectively learn the preference weights of various applications executed and prioritizations for key QoS parameters affecting strategy-making of robots; and (3) we apply the game-theoretic approach to devise a symbiotic robotics computation offloading algorithm named SyRoC, which operates in a distributed manner to solve the optimization problem and determine the most effective strategies. To validate our scheme, we conduct a series of experiments on the software simulator, which demonstrate that our proposed scheme not only realizes stable performance on guaranteeing convergence and system utility when robots move dynamically, but also outperforms five typical algorithms in key metrics such as energy consumption (13.43%↓), delay (14.22%↓), and average QoS utility of robots corresponding to the four types of applications executed (12.80%↑, 7.30% ↑, 7.90% ↑,and12.71%↑) in scenarios involving the expansion of robot scales.

An analytical model for multihop LoRaWAN networks

LoRaWAN is one of the most popular LPWAN technology due to the facility to implement applications that require a low cost, low energy consumption, low data rate, and large coverage area. LoRaWAN is a single-hop star-of-stars topology composed of end-devices that transmit data to be collected by gateways in the coverage area. Multihop networks are receiving the attention of the LoRaWAN community since it allows to extend the coverage area and improve energy efficiency, thus prolonging the network lifetime. In this paper, we propose an analytical model for multihop LoRaWAN networks. The objective of the analytical model is to provide a general and theoretical definition of a multihop LoRaWAN network, considering different device characteristics and network topologies. The analytical model gives new insights into the performance of multihop LoRaWAN networks. We investigate the energy consumption, throughput, delay, and packet delivery ratio of single-hop and multihop relay networks. The results showed that the relay network increases the network performance compared to the regular LoRaWAN network, although there are some limitations on the number of hops and relay characteristics. The development and deployment of multihop LoRaWAN networks are creating new opportunities, and the analytical model presented could be used before real deployments for a better knowledge of limitations and network needs.

Parallel Finite Field Algorithms for Communications and Sensor Networks

Sensor network integrates sensor technology, embedded computing technology, modern network and wireless communication technology, distributed information processing technology, etc. It can monitor, perceive and collect the information of various environments or monitoring objects in real time through various integrated micro sensors, and process the information through the embedded system. The perceived information is transmitted to the user terminal by multi-hop relay through the random ad-hoc wireless communication network. The coding of communications and sensor networks affects the efficiency of communication. The main coding technology is based on finite field. Among operations in finite fields, divisions are time-consuming operations since they are generally computed via inversions and multiplications. We present techniques to exploit extend binary trees for fast divisions in finite fields. We implement the finite field algorithm on Field Programmable Logic Arrays (FPGAs) in a parallel way. The implementation result from FPGAs shows that the parallel finite field algorithm can speed up the process of coding of communications and sensor networks.

An intelligent dimension-based cat swarm optimization for efficient cooperative multi-hop relay selection in vehicular network

An intelligent dimension-based cat swarm optimization for efficient cooperative multi-hop relay selection in vehicular network

ENERGY EFFICIENT MULTI-HOP CLUSTER BASED D2D COMMUNICATION FOR CATASTROPHIC AREA

: Earth has been experiencing different types of disasters since time immemorial, causing death and destruction (to all types of infrastructure). Different parts of the world have been devastated by cyclones, earthquakes, landslides, and tornadoes. Over the past few years, energy and resource management has been the goal of research. Device-to-device communication is one of the emerging technologies that have the potential to play a crucial role in natural disasters by utilizing direct D2D communication to help achieve specific goals. Communication between D2D devices was designed for short-range use but can be applied to longrange applications through multi-hop relays. In addition, it is applicable to a number of practical applications including disaster management, uncoverage areas in cells, and battlefields. In order to optimize energy balancing and resource utilization, a cluster-based channel allocation scheme was used. Our communication infrastructure can work independently in case of any natural disaster, where primary infrastructure is damaged or not available. The proposed scheme "relays the communication traffic to the nearest base station through multiple hops. We applied the Dijkstra algorithm for the shortest path calculation. In order to calculate linkages from the source to the destination and to send data over reliable channels, the Link Calculation Method (LCM) is employed before transmitting frames. Our RF energy harvesting mechanism HSEH ensures energy is harvested from the most efficient source for maximum efficiency. The high strength signal of the RF source continues to ensure that energy is being harvested. Finally, we compared our simulation results with existing schemes. Results indicate that the proposed scheme outperforms the existing schemes in terms of consuming less energy while transmitting the data through a more reliable channel.

Event-Triggered Approximate Byzantine Consensus With Multi-Hop Communication

In this paper, we consider a resilient consensus problem for the multi-agent network where some of the agents are subject to Byzantine attacks and may transmit erroneous state values to their neighbors. In particular, we develop two event-triggered update schemes to tackle this problem as well as reduce the communication for each agent. Our approach is based on the mean subsequence reduced (MSR) algorithm with agents being capable to communicate with multi-hop neighbors through relaying process. Since communication delays are critical in such an environment, we provide necessary graph conditions for the proposed algorithms to perform well with delays in the communication. Moreover, a novel multi-hop relay scheme with event-triggered feature is proposed. It can reduce more transmissions than the conventional one-hop event-triggered algorithm. We also highlight that through multi-hop communication, the network connectivity can be reduced especially in comparison with the common one-hop communication case. Lastly, we show the effectiveness of the proposed algorithms by numerical examples.

Joint Relay Selection and Resource Allocation for Delay-Sensitive Traffic in Multi-Hop Relay Networks

Joint Relay Selection and Resource Allocation for Delay-Sensitive Traffic in Multi-Hop Relay Networks

Performance Study and Optimization of 3D-MANET: A New Analytical Perspective Based on Zipf’s Law

This paper studies the throughput capacity and delay scaling laws in a three-dimensional mobile ad hoc network (3D-MANET) under different routing schemes. Previous work generally assumed that nodes follow a uniform distribution or a power-law distribution to move in the network. From the perspective of the entire network, it is difficult for this network model to reflect communication entities’ distribution in real 3D space. Moreover, the research results of analyzing network performance using different routing schemes are limited, and the research work is insufficient. With formerly related studies different,we propose a cell-gridded network model that considers the actual environment with cells of the node aggregation degree, which follows Zipf’s law with exponent γ . And our model can cover a variety of distribution scenarios with changes in the γ value. The packet delivery rate, network capacity, and delay performance of 3D-MANET adopting the traditional two-hop nonredundant and redundant relay routing scheme are examined utilizing theoretical tools such as probability theory, random process, and queuing theory. We propose a wireless access point- (WAP-) enabled multihop relay routing scheme. By deploying WAP in cells with a high γ , nodes can access WAP and broadcast packets, which accelerates the delivery of packets, and the results obtained by applying this scheme indicate that compared with the two-hop relay scheme, the WAP multihop relay effectively improves the delay performance and the transmission efficiency with less loss of capacity performance. Additionally, a better delay-capacity trade-off performance is achieved. Finally, we discuss the influence of parameters such as the number of network nodes n , the number of network cells m , the redundancy r , and γ on the capacity and delay. The analysis results confirm that exploiting the users’ distribution status information and dividing the cells reasonably will save deployment costs and further improve network performance.

Performance analysis and optimization of energy harvesting cognitive multi-hop relay network over mixed Rayleigh and double-Rayleigh fading channels

In this paper, we investigate the outage performance of an energy harvesting underlay cognitive multi-hop relay network. In the network, energy-constrained secondary network (SN) nodes harvest energy from radio frequency signal of a power beacon (PB) node. The source node transmits information to destination node via multiple intermediate relay nodes by using a time division broadcast protocol, and the hardware impairments of SN nodes’ transceiver are modeled. The outage performance of SN is analyzed and evaluated by accurately approximate and asymptotic closed-form expressions of outage probability (OP) over quasi-static mixed Rayleigh and double-Rayleigh fading channels. Additionally, due to the complexity of OP expression, a chaotic dragonfly algorithm (CDA) is proposed to jointly optimize energy harvesting ratio and PB node’s abscissa, which can achieve OP minimization of SN. Extensive simulations demonstrate the correctness of theoretical analysis and the effectiveness of the proposed CDA.

Secure and Energy-Efficient UAV Relay Communications Exploiting Collaborative Beamforming

Unmanned aerial vehicle (UAV) is a promising communication platform to assist terrestrial networks. In this work, we aim to provide relay communication to the blocked or low-quality terrestrial networks via an aerial relay. Nevertheless, major issues of the considered system are the worrying security and limited service time. Thus, we study a novel aerial relay system via collaborative beamforming (CB) by exploiting a UAV-enabled virtual antenna array (UVAA) to achieve a secure and energy-efficient communication for remote ground users (GUs). Specifically, we formulate a secure and energy-efficient communication multi-objective optimization problem (SECMOP) to circumvent the effects of the known and unknown eavesdroppers and minimize the propulsion energy consumption of UAVs, by optimizing the hovering positions and excitation current weights of UAVs and the scheduling for communicating with the remote GUs. The formulated SECMOP is challenging and proven to be NP-hard. Thus, we propose an improved evolutionary computation method with several enhanced designs to solve this problem. Simulation results demonstrate the benefits of the proposed IMODAOM against various benchmark algorithms. Moreover, we find that the UVAA-based relay can achieve substantial energy consumption reduction as compared to the multi-hop relay scheme.

Optimal Routing for Multi-User Multi-Hop Relay Networks Via Dynamic Programming

In this letter, we study the relay selection problem in multi-user, multi-hop relay networks with the objective of minimizing the network outage probability. When only one user is present, it is well known that the optimal relay selection problem can be solved efficiently via dynamic programming. This solution breaks down in the multi-user scenario due to dependence between users. We resolve this challenge using a novel relay aggregation approach. On the expanded trellis, dynamic programming can be used to solve the optimal relay selection problem with computational complexity linear in the number of hops. Numerical examples illustrate the efficient use of this algorithm for relay networks.

AquaStream: Multihop Multimedia Streaming Over Acoustic Channel in Severely Resource-Constrained IoT Networks

Robust and reliable communication systems, whether based on electromagnetic (EM) waves or light, fail to perform under water due to very high attenuation and changing visibility conditions. The present generation of systems designed for underwater communications relies mostly on acoustic waves, typically in the ultrasonic frequency range. In this work, we develop and evaluate a means of implementing underwater acoustic channel-based severely constrained IoT networks using low-cost, off-the-shelf, open hardware electronics and transducers, which can support direct communication between two nodes at a data rate of 2.4 kbps for over 65 m. These nodes can be deployed over much longer distances through multihop relay topologies. Furthermore, we evaluate the efficacy of our system toward supporting multimedia data transmission and even attempt multimedia streaming through our deployed underwater IoT network using video compression and reduced sampling of the video frames. We observe that the system successfully supports multihop network topologies and undertakes multimedia transmission by compromising the quality of the data. The system has a clear tradeoff between data quality, transmission range, and transmission delays.

Data Cooperative Distribution Mechanism of Internet of Vehicles Using D2D Technology

In recent years, with the advancement of the automotive industry and the innovation of electronic technology, issues related to the field of Internet of Vehicles (IoV for short) have received increasing attention. Existing communication technologies can no longer meet the demands of high mobility, low latency, high reliability, and massive streaming data distribution faced by IoV in the future. As one of the key technologies of 5G, D2D communication technology can effectively alleviate the above challenges faced by IoV. This technology not only allows terminals to perform point-to-point direct communication within a certain range but also allows data forwarding between receiving terminals, thereby improving the data distribution efficiency of the IoV, which injects new impetus into the development of the IoV business in the future. However, existing cooperative distribution algorithms between terminals do not fully consider the differences in D2D links, making it difficult to achieve efficient use of spectrum resources. To address this problem, this paper proposes a cooperative data distribution algorithm based on multihop relay in the IoV environment where D2D is used to realize flexible terminal communication between vehicles, including both multicast and unicast modes. The algorithm adaptively selects the optimal relay, route, and number of transmission hops based on the D2D link quality to find the optimal cooperative distribution scheme to achieve the goal of optimizing the energy efficiency of the requesting vehicle. Simulation results show that, compared with the existing one-hop unicast and one-hop multicast forwarding algorithms, the multihop relay data cooperative distribution algorithm proposed in this paper exhibits strong global optimization ability and can significantly improve D2D forwarding resource utilization and data transmission rate and improve the throughput of data distribution services, thereby effectively improving the energy efficiency of the requesting vehicle.

Performance Analysis and Optimization of Multihop MIMO Relay Networks in Short-Packet Communications

This work investigates the multiple-input multiple-output system in the context of the selective decode-and-forward multihop relay network under short-packet communications to facilitate not only ultra-reliability, but also low-latency communications. For the transmit and receive diversity techniques, we analyze the transmit antenna selection (TAS) and maximum-ratio transmission (MRT) schemes at the transmit side, whereas the selection-combining (SC) and maximum-ratio combining (MRC) schemes are leveraged at the receive side. For quasi-static Rayleigh fading channels and the finite-blocklength regime, we derive the approximate closed-form expressions of the end-to-end (e2e) block error rate (BLER) for the TAS/MRC, TAS/SC, and MRT/MRC schemes. The asymptotic performance in the high signal-to-noise ratio regime is derived, from which the comparison among diversity schemes in terms of the diversity order, e2e BLER loss, and SNR gap is provided. Furthermore, based on the asymptotic results, we develop power-allocation, relay-location, and joint simplified optimizations to minimize the asymptotic e2e BLER under the system constraints. The e2e latency and throughputs are also analyzed for the considered schemes. The correctness of our analysis is confirmed via Monte Carlo simulations.

Secure and Efficient Distributed Relay-Based Rekeying Algorithm for Group Communication in Mobile Multihop Relay Network

In mobile multihop relay (MMR) networks, Relay multicast rekeying algorithm (RMRA) is meant to ensure secure multicast communication and selective updating of keys in MMR networks. However, in RMRA, the rekeying is carried out after a specific interval of time, which cannot ensure the security for multicast communication on joining the member. Secondly, the rekeying scheme generates a huge communication overhead on the serving multihop relay base station (MR-BS) on frequent joining of members. Lastly, there is nothing about when a member left the group communication. Thus, the rekeying scheme of RMRA fails to provide forward and backward secrecy and also is not scalable. To solve this problem, an improved rekeying scheme based on broadcasting a new seed value on joining and leaving of a member for updating the ongoing key management is proposed. The proposed scheme solves the issue of forward and backward secrecy and the scalability in a very simplified way. The forward and backward secrecy of the proposed scheme has been extensively validated by formal method using rank theorem. Furthermore, mathematical derivation showed that the proposed scheme out-performed the RMRA in terms of communication cost and complexity.