Relay Path Research Articles

Deep Learning Based Cooperative MIMO Systems for Wireless Body Area Networks

Wireless Body Area Network (WBAN) is widely applied in various fields, including healthcare, sports, wellness, and assistive technologies, by offering the benefits of convenience, reliability, low latency, privacy, and customization. However, the propagation characteristics of the WBAN channel can impact the reliability of transmission, which is particularly crucial in healthcare systems. To address this issue, this article presents a novel approach using deep learning-based cooperative Multiple-Input Multiple-Output (MIMO) systems that leverage the autoencoder (AE) technique. In our proposed approach, we utilize the AE-based cooperative MIMO systems with two different techniques: Amplify-and-Forward (AE-AF) and Decode-and-Forward (AE-DF). The AE-AF scheme operates without needing training parameters at the relay node, whereas the AE-DF scheme necessitates training parameters at the relay node. Both schemes aim to overcome challenges such as multipath propagation phenomena, thereby enhancing the performance of on-body communication systems. Additionally, we introduce two combinators, Minimum Mean Square Error (MMSE) scheme and Radio Transformation Network (RTN), to effectively mitigate co-channel interference (CCI) in the received signal streams and improve the bit error rate performance of the AE-AF and AE-DF systems. We assess the performance of these systems in scenarios with and without direct links. Simulation results demonstrate significant performance improvements compared to baseline cooperative MIMO systems using MMSE combining, namely AF-MMSE and DF-MMSE systems. Notably, the proposed systems employing RTN combination, including both direct and relay paths, achieve a 7.5 dB gain over the baseline when all nodes are equipped with two transceiver antennas.

Multipoint Relay Path for Efficient Topology Maintenance Algorithm in Optimized Link State Routing-Based for VANET

The Optimal Link State Routing (OLSR) protocol employs multipoint relay (MPR) nodes to disseminate topology control (TC) messages, enabling network topology discovery and maintenance. However, this approach increases control overhead and leads to wasted network bandwidth in stable topology scenarios due to fixed flooding periods. To address these challenges, this paper presents an Efficient Topology Maintenance Algorithm (ETM-OLSR) for Enhanced Link-State Routing Protocols. By reducing the number of MPR nodes, TC message generation and forwarding frequency are minimized. Furthermore, the algorithm selects a smaller subset of TC messages based on the changes in the MPR selection set from the previous cycle, adapting to stable and fluctuating network conditions. Additionally, the sending cycle of TC messages is dynamically adjusted in response to network topology changes. Simulation results demonstrate that the ETM-OLSR algorithm effectively reduces network control overhead, minimizes end-to-end delay, and improves network throughput compared to traditional OLSR and HTR-OLSR algorithms.

UAV relay network deployment through the area with barriers

Flying ad hoc networks composed of Unmanned Aerial Vehicles (UAVs) are flexible, inexpensive, and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a multi-hop communication link between the UAVs is a challenging task. The existing network deployment method designed for relay network may fail to guarantee the connectivity due to the limited wireless transmission and dynamic topology. Designing and implementing a cost-effective UAV relay network is still a problem when there are barriers between the source node and the ground control station. In this paper, we first build a general UAV relay network model; then we propose a UAV deployment algorithm based on Q-learning to construct a UAV relay network with the minimum number of nodes, and we use an Equidistant Node Control algorithm to construct a dynamic relay path. We conduct a series of experiments on the OMNeT++ simulation platform to evaluate the performance of our proposed algorithm. The experimental results show that our UAV relay network has the lower cost and reliable communication performance.

A Multipath Data-Scheduling Strategy Based on Path Correlation for Information-Centric Networking

Information-Centric Networking (ICN) has revolutionized the manner of content acquisition by shifting the communication mode from host-centric to information-centric. Considering the existing, large amount of IP infrastructure in current networks, the new ICN architecture is proposed to be compatible with existing networks in order to reduce deployment cost. However, due to compatibility with IP networks, ICN data packets must be transmitted through the default path provided by IP routing regulations, which also limits the transmission efficiency and reliability of ICN. In order to address this issue, this paper introduces a multipath transmission method applied in ICN which takes full advantage of the functions and characteristics of ICN and builds multiple end-to-end relay paths by using the ICN routers as relay nodes. We then propose a relay-node-selection algorithm based on path correlation to minimize the impact of overlapping links. Moreover, we comprehensively calculate the path state value by combining the round-trip time and packet loss rate and propose a multipath data-scheduling algorithm based on the path state value. Simulation experiments show that the proposed method can maintain high bandwidth utilization while reducing the number of out-of-order packets.

Concurrent multipath quantum entanglement routing based on segment routing in quantum hybrid networks

In the future, quantum networks will be an important development direction. Quantum networks should be studied considering quantum's unique physical properties. In quantum networks with limited resources, decoherence will lead to qubits loss, which restricts the time that data qubits can be stored in memory before use. To realize the network function, it is very important to transmit data qubits as quickly as possible. In order to ensure timeliness and make use of entanglement resources as much as possible, this paper proposes a concurrent multipath entanglement routing scheme based on segment routing for quantum hybrid networks. In this scheme, centralized routing is used to calculate the “segments” of quantum relay path, and distributed routing is used to transmit control messages between the “segments”. The “concurrent” mechanism is fully adopted in classical messages passing, path nodes BSM (Bell State Measurement) execution and multipath shunt transmission. This scheme has obvious advantages in multipath concurrent transmission, traffic diversion, reducing transmission time and providing redundancy.

Joint Flying Relay Location and Routing Optimization for 6G UAV–IoT Networks: A Graph Neural Network-Based Approach

Unmanned aerial vehicles (UAVs) are widely used in Internet-of-Things (IoT) networks, especially in remote areas where communication infrastructure is unavailable, due to flexibility and low cost. However, the joint optimization of locations of UAVs and relay path selection can be very challenging, especially when the numbers of IoT devices and UAVs are very large. In this paper, we formulate the joint optimization of UAV locations and relay paths in UAV-relayed IoT networks as a graph problem, and propose a graph neural network (GNN)-based approach to solve it in an efficient and scalable way. In the training procedure, we design a reinforcement learning-based relay GNN (RGNN) to select the best relay path for each user. The theoretical analysis shows that the time complexity of RGNN is two orders lower than the conventional optimization method. Then, we jointly exploit location GNN (LGNN) and RGNN trained to optimize the locations of all UAVs. Both GNNs can be trained without relying on the training data, which is usually unavailable in the context of wireless networks. In inference procedure, LGNN is first used to optimize the location of UAVs, and then RGNN is used to select the best relay path based on the output of LGNN. Simulation results show that the proposed approach can achieve comparable performance to brute-force search with much lower time complexity when the network is relatively small. Remarkably, the proposed approach is highly scalable to large-scale networks and adaptable to dynamics in the environment, which can hardly be achieved using conventional methods.

Relay Selection and Secure Connectivity Analysis in Energy Harvesting Multi-Hop D2D Networks

The relay is harvesting energy for data transmission and eavesdropping attacks will occur. Considering carried energy and security of relay, this letter studies relay selection in energy harvesting multi-hop D2D networks with an eavesdropper. To improve the secure connectivity performance of the relay, the higher bound of source-to-destination secrecy connectivity probability (SCP) is derived. Then, we derive the factor directly related to the largest SCP. Then, a relay selection algorithm is proposed to find a higher security connectivity relay path. Our theoretical derivation and the proposed algorithm are verified by Monte Carlo simulation results. The simulation results show that the proposed algorithm exhibit significantly higher SCP than the direct transmission method and conventional relay selection algorithms.

Performance Analysis of AF Cooperative Relaying Networks with SWIPT

Cooperative communication networks have received more attention due to its ability to improve the signal quality of terminal devices by spatial diversity. Under recent advance in internet of things, In order to extend the service life of terminal devices powered by battery, simultaneous wireless information and power transfer (SWIPT) technique has been emphasize. The terminal devices can harvest energy and decode information from the same radio frequency (RF) signal using by SWIPT technique. In this paper, we combine both techniques to study the performance of both conventional cooperative relaying networks without SWIPT and cooperative relaying networks with SWIPT under an amplify-and-forward (AF) relaying network. To the best of our knowledge, no one simultaneously studies and compares the performance of both systems. Therefore, the outage probabilities of both systems are carried out, and numerical results are compared in this paper. The main results include: (1) Compared with conventional cooperative communication, the cooperative communication with SWIPT has better outage probability only when the distance between relay node and source node is less than one. It implies that, to outperform the conventional cooperative communication, the relay node should harvest enough energy for signal transmission. (2) With the diversity of direct path and relay path, the outage probability of cooperative communication with EH under an AF relaying network has been significantly reduced.

Opportunistic Data Relay Scheme for Narrowband Multihop Combat Radio Networks

In this paper, we propose an opportunistic data relay scheme in narrowband multihop combat radio networks. Narrowband networks have physical restrictions on high-speed transmission. Furthermore, the topology changes dynamically due to the jamming of the enemy, signal interference between friendly forces, and movement of network entities. Therefore, the traditional relay scheme that collects topology information and calculates a relay path before transmission is unsuitable for such networks. Our proposed scheme does not collect topology information and transmits data opportunistically. The scheme can cause unnecessary data relaying that is not related to data delivery to the destination node. However, for small networks, the effect of increasing network throughput by not gathering topology information is much greater than the effect of reducing throughput by unnecessary data relays. We demonstrate the performance superiority of the proposed scheme through simulation in the worst case of network topology.

Impact of channel correlation on network coded cooperation with two sources

In this paper, we consider Digital Network Coded Cooperation (DNCC) with Decode-and-Forward (DF) relaying scheme in correlated environment. In order to quantify the performance of DNCC network, analytical closed form expression of the outage probability for Non-Line of Sight (NLoS) correlated environments is derived. For the sake of completeness and comparison, investigation of uncorrelated environments is also presented. Unlike existing investigations, it is observed that spatial correlation among channels considerably improves the performance of such networks. In particular, detrimental effects of the Digital Network Coding (DNC) noise is abated by the channel correlation. Additionally a discussion on various deterministic geometries for such networks is also presented to get further insights about node placement. Cumulative Distribution Function (CDF) obtained for Signal to Noise Ratio (SNR) of relay path can be utilized for performing diversity calculations. Outage closed form expressions derived may be used to choose network parameters judiciously in different NLoS correlated scenarios for achieving better Quality of Service (QoS) in next generation wireless networks.

Energy-efficient cluster head selection through relay approach for WSN

In the clustering method, the cluster head node loses much energy between transmissions to the base station, confirming that determining the cluster heads is crucial. A robust determination protocol needs to pick cluster heads depending on the node's region and its residual energy. We proposed an innovative approach to the method of selecting cluster heads in this work. The target of the cluster head depends on node distance and node energy. The cluster head selection aims to minimise energy utilisation and to enhance the lifetime of the networking by introducing the shortest path relay node concept. When few subcluster nodes are heavily loaded, this results in faster energy consumption, and to achieve normal energy depletion, the selected trajectory cluster is launched. The distances among the clusters decide and play an important part in energy consumption. As a result, the shortest path selection relay approach leads to the nominal depletion of the energy of each node present in the array to create a transmission with nearest nodes in the shortest path between the heads of the source cluster.

Mathematical framework for 5G‐UAV relay

AbstractUnmanned aerial vehicle's (UAVs) small size, long‐lasting battery, and flexible trajectory have produced widespread applications in radio communication systems, especially its usage as a cellular tower (gNB) for 5G services. At the same time, the mmWave's enormous available bandwidth makes it the primary contender for next‐generation communication networks. This article aims to synthesize and assess the usage of mmWave concurrently in backhaul and access links for amplify‐and‐forward (AF) relay installed on the UAV. A mathematical framework is developed for the received power of the user equipment (UE) obtained in relay path (gNB‐UAV‐UE) and direct path (gNB‐UE) via; (i) free space, and (ii) log‐distance path loss model. The International Telecommunication Union recommended city model is used to assess the likelihood for LoS and NLoS paths in four urban environments; (i) high‐rise urban, (ii) dense urban, (iii) urban, and (iv) suburban. Furthermore, various parameters, that is, UAV's position and amplification factor are stipulated to optimize the efficiency of a UAV‐based AF relay for enhanced users coverage.

Joint link-level and network-level reconfiguration for urban mmWave wireless backhaul networks

Due to the rapid densification of small cells in 5G and beyond cellular networks, deploying wired high-bandwidth connections to every small cell base station (BS) is difficult, particularly in older metropolitan areas where infrastructure for fiber deployment is lacking. For this reason, mmWave wireless backhaul has been proposed as a cost-effective and flexible alternative that has the potential to support the high data rates needed to accommodate backhaul traffic demands. To address the robustness of such networks, we investigate a novel relay-assisted backhaul architecture, where a number of small-cell BSs and relays are deployed, e.g. on the lampposts of urban streets. In this scenario, the interconnected logical links constitute a mesh network, which offers opportunities for both link-level and network-level reconfiguration to overcome blockages and/or node failures. We present two joint link-network level reconfiguration schemes for recovery after exceptional events. One prioritizes relay path (link-level) reconfiguration and uses alternate network-level paths only if necessary. The other splits traffic on both reconfigured logical links and backup network paths to improve throughput. Through simulation, the reconfiguration schemes are shown to not only provide near-optimal backhaul survivability but to also maintain high network throughput across a range of scenarios for urban mmWave backhaul networks. The schemes are also validated to significantly outperform existing purely link-level and purely network-level reconfiguration schemes.

An Adaptive Neuro Fuzzy Inference System (ANFIS) Based Relay Selection Scheme for Cooperative Wireless Sensor Network

Cooperative communication in wireless sensor network has emerged a solution of energy limitation of sensor nodes. Relay selection in cooperative communication plays an important role to improve the performance of energy constrained networks. In such networks, to make balance between network lifetime (NL) and Bit Error Rate (BER) is the difficult task for the researchers. Although, the minimization of BER can be achieved by choosing best possible relay to destination link which has lowest path loss, but this solution cannot gives guarantee to enhance the NL because some nodes are frequently selected for retransmission of the information. On the other hand, increase the NL is possible by efficiently distribution of energy consumption among all the available relay nodes. In this paper, we propose an Adaptive Neuro Fuzzy Inference System based Relay Selection (ANFISRS) scheme where residual energy of the relay node and path loss of the channel are considered as an input parameters for the relay selection. ANFISRS makes balance between these two parameters for improving network lifetime and BER. Furthermore, the proposed method is compared with three existing strategies: Random Relay Selection, Maximum Residual energy based Relay Selection, and Minimum Energy Consumption based relay selection. The proposed scheme considerably reduces the BER while enhance the network lifetime over the existing strategies.

Bit error probability analysis of IR-UWB ED-OOK system using cooperative dual-hop DTF strategy

The Bit Error Rate (BER) of a single user cooperative Impulse Radio (IR)-Ultrawideband (UWB) communication system employing Energy Detector (ED) receiver with On-Off Keying (OOK) in IEEE 802.15.4a UWB multipath environment is investigated in this paper. Analytical evaluation based on Energy detection principle is performed to derive approximate BER Expressions for various diversity combining cases, namely optimum combining, linear combining and selective combining using cooperative dual-hop Detect and Forward (DTF) relay protocol in presence and absence of Inter-symbol interference (ISI). Numerical results reveal that there is a significant improvement in BER, with increase in number of relay diversity paths and decrease in number of frames Nf. The accuracy and perfection in approximation used in investigation of BER is confirmed with the validation of the analytical BER expressions with that of the simulation results. The analytical and simulation results confirm that among the diversity combining schemes, the performance of optimum combining is better compared with linear combining, which in turn performs better than selective combining.

Generalized Path–Permutation Codes for Reliable End-to-End Networking of Opportunistic Links

Opportunistic links are emerging as a novel technology for state-of-the-art wireless networks, such as cognitive radio networks, energy-harvesting networks, and low-latency vehicular networks. To increase the reliability of these networks, path-permutation codes (PPCs) were advocated in [1] . These codes are based on a virtual multiple-input multiple-output (MIMO) model on the session/network layer, and have been tailored for increased reliability of opportunistic links. By exploiting multipath–multihop routes, PPCs access one relay path at a time while repeatedly transmitting the same QAM symbol. In this paper, we introduce a generalized PPC scheme which simultaneously accesses multiple relay paths and comprises multiple QAM symbols in the packet. Phase rotations are also introduced in the PPC codewords for additional performance improvement. Numerical simulation results validate our analyses and demonstrate the superior performance of this novel coding scheme, i.e., better error rate performance, higher throughput, and stronger robustness to transmission outages.

Performance Evaluation of Next-Generation Wireless (5G) UAV Relay

Future wireless communication, especially the densified 5G network using millimeter-Wave (mmWave) will bring numerous innovations to the current telecommunication industry. In such scenario, the use of Unmanned Aerial Vehicle (UAV) as Base Station (BS) becomes one of the viable options for providing 5G services. The focus of this study is to investigate, analyze and describe the distinctive rich characteristics of mmWave propagation in Access and backhaul network simultaneously using UAV. The mathematical framework is formulated for calculating UE (User Equipment) received power for the relay path (BS–UAV–UE) based on Friis Transmission Equation. We conduct simulations using the ray-tracing simulator in different scenarios while comparing and verifying the simulation results vs mathematical equations. Using ray racing simulator, the effectiveness of diffracted, reflected, and scattered paths versus direct paths is described. Furthermore, using extensive simulations, we highlight the impact of UAV location to maximize the performance of an Amplify-and-Forward UAV based relay for providing enhanced coverage to the users.

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.

A Continuum Model for Route Optimization in Large-Scale Inhomogeneous Multi-Hop Wireless Networks

Multi-hop route optimization in large-scale inhomogeneous networks is typically NP-hard, for most problem formulations, requiring the application of heuristics which, despite their relatively low processing complexity, find suboptimal solutions. Where optimal solutions can be determined by Lagrangian based constrained optimization techniques for example, the processing complexity typically scales like O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ), N being the number of relays employed. Here, we propose an alternative approach to route optimization by considering the limit of infinite relay node density to develop a continuum model, which yields an optimized equivalent continuous relay path. The model is carefully constructed to maintain a constant connection density even though the node density scales without bound. This leads to a formulation for minimizing the end-to-end outage probability that can be solved using methods from the calculus of variations. With the continuum model, we show that the processing complexity scales linearly with the number of points that sample the continuous path, which can be lower than the number of relay nodes in a large scale network. We demonstrate the effectiveness of this new approach and its potential by considering a network subjected to point sources of interference.

Copper relay path through the N-terminus of Wilson disease protein, ATP7B

In human cells, copper (Cu) ions are transported by the cytoplasmic Cu chaperone Atox1 to the Wilson disease protein (ATP7B) in the Golgi for loading of Cu-dependent enzymes. ATP7B is a membrane-spanning protein which, in contrast to non-mammalian homologs, has six cytoplasmic metal-binding domains (MBDs). To address the reason for multiple MBDs, we introduced strategic mutations in which one, two or three MBDs had been blocked for Cu binding via cysteine-to-serine mutations (but all six MBDs are present in all) in a yeast system that probes Cu flow through Atox1 and ATP7B. The results, combined with earlier work, support a mechanistic model in which MBD1-3 forms a regulatory unit of ATP7B Cu transport. Cu delivery via Atox1 to this unit, followed by loading of Cu in MBD3, promotes release of inhibitory interactions. Whereas the Cu site in MBD4 can be mutated without a large effect, an intact Cu site in either MBD5 or MBD6 is required for Cu transport. All MBDs, expressed as single-domain proteins, can replace Atox1 and deliver Cu to full-length ATP7B. However, only MBD6 can deliver Cu to truncated ATP7B where all six MBDs are removed, suggesting a docking role for this structural unit.