Cooperative Communication Networks Research Articles

Performance analysis of a cooperative D2D communication network with NOMA

The cooperative device-to-device (D2D) network employing non-orthogonal multiple access (NOMA) is expected to play an important role in the next-generation wireless networks. In this work, the authors derive outage probability expressions of a cooperative NOMA D2D network which employs decode-and-forward relaying. A wireless link experiencing Nakagami-m fading is considered which is further assisted in the communication network by a wired link which is a powerline communication link and experiences Rayleigh fading. The outage analysis, shown for both the strong user and the weak user, is derived assuming that at the receiver there is perfect successive interference cancellation. Employing power division NOMA, optimum value for the coefficient of power allocation is obtained corresponding to the minimum probability of outage of the strong user. Furthermore, a range of the NOMA power allocation coefficient is provided for the communication link at the weak user which is between the wireless and the powerline link. Symbol error probability expressions are also derived for the strong and the weak users for the scenario when: i) both the wireless and the wired links are available for communication and ii) only the wireless link is available for communication.

An Optimal Power Allocation Scheme for Cooperative Communication Network with Non-Orthogonal Multiple Access

An Optimal Power Allocation Scheme for Cooperative Communication Network with Non-Orthogonal Multiple Access

Relay Selection, Scheduling, and Power Control in Wireless-Powered Cooperative Communication Networks

Relay nodes are used to improve the throughput, delay and reliability performance of energy harvesting networks by assisting both energy and information transfer between sources and access point. Previous studies on radio frequency energy harvesting networks are limited to single-source-single/multiple-relay networks. In this paper, a novel joint relay selection, scheduling and power control problem for multiple-source-multiple-relay network is formulated with the objective of minimizing the total duration of wireless power and information transfer. The formulated problem is non-convex mixed-integer non-linear programming problem, and proven to be NP-hard. We first formulate a sub-problem on scheduling and power control for a given relay selection. We propose an efficient optimal algorithm based on a bi-level optimization over power transfer time allocation. Then, for optimal relay selection, we present optimal exponential-time Branch-and-Bound (BB) based algorithm where the nodes are pruned with problem specific lower and upper bounds. We also provide two BB-based heuristic approaches limiting the number of branches generated from a BB-node, and a relay criterion based lower complexity heuristic algorithm. The proposed algorithms are demonstrated to outperform conventional harvest-then-cooperate approaches with up to 87% lower schedule length for various network settings with at least 7.88 times higher algorithm runtime.

Reweighted l p constraint LMS‐based adaptive sparse channel estimation for cooperative communication system

The issue of sparsity adaptive channel reconstruction in time-varying cooperative communication networks through the amplify-and-forward transmission scheme is studied. A new sparsity adaptive system identification method is proposed, namely reweighted l p norm ( 0 < p < 1 ) penalised least mean square (LMS) algorithm. The main idea of the algorithm is to add a l p norm penalty of sparsity into the cost function of the LMS algorithm. By doing so, the weight factor becomes a balance parameter of the associated l p norm adaptive sparse system identification. Subsequently, the steady state of the coefficient misalignment vector is derived theoretically, with a performance upper bounds provided which serve as a sufficient condition for the LMS channel estimation of the precise reweighted l p norm. With the upper bounds, the authors prove that the l p ( 0 < p < 1 ) norm sparsity inducing cost function is superior to the reweighted l 1 norm. An optimal selection of p for the l p norm problem is studied to recover various d sparse channel vectors. Several experiments verify that the simulation results agree well with the theoretical analysis, and thus demonstrate that the proposed algorithm has a better convergence speed and better steady-state behaviour than other LMS algorithms.

Cooperative Residual Battery (CORB) Resource Optimization in AODV Routing Protocol

In Ad-hoc network minimizing the energy utilization is one of the core issues in transmission of data with entail quality of service. Cooperative communication networks have been recently being studied as an alternative to MIMO wireless networks where cooperation between source destination and relay are considered. In this paper, Cooperative Residual Battery (CORB) Resource Optimization routing protocol is proposed in which the route formation in cooperative network from source to destination is established by selecting the minimum battery consuming node as relay. Packet reception ratio is considered for efficiently switching between the direct communication and cooperative communication depending on the type of scenario’s that occur in real time. The proposed work is based on the modification done on AODV protocol. The relay selection in cooperative communication is established based on least hop count and residual battery life of a node. The protocol is mainly based on selecting a helper node from a list of intermediate nodes that are consuming less energy to forward the data on to the destination. Considerable modification in Route request and Route reply packet is done in order to carry the Residual battery information of nodes that are handling the Control packets (RREQ &amp; RREP), along with the control packets, routing table is modified for managing the routing information. Simulation is carried out to assess the essence of the protocol proposed.

AI for dynamic packet size optimization of batteryless IoT nodes: a case study for wireless body area sensor networks

Packet size optimization, with the purpose of minimizing the wireless packet transmission energy consumption, is crucial for the energy efficiency of the Internet of Things nodes. Meanwhile, energy scavenging from ambient energy sources has gained a significant attraction to avoid battery issues as the number of nodes increasingly grows. Packet size optimization algorithms have so far been proposed for battery-powered networks that have limited total energy with continuous power availability to prolong their lifetime. On the other hand, batteryless networks based on energy harvesting offer unlimited total energy with the interruption in availability. This is due to changing ambient conditions or the required time for harvesting and storing in small capacitors. Packet size optimization of batteryless networks has not been addressed so far. In this paper, an AI-based packet size optimization algorithm is proposed for batteryless networks that consider the amount of harvested energy at each node. Therefore, packet size is optimized dynamically for each round of data transmission. The proposed method is then evaluated via numerical simulations for a heterogenous wireless body area sensor network as a case study, considering 1-hop, cooperative, and 2-hop communication networks. Cooperative topology yields optimum energy efficiency for highly dynamic sensors, such as ECG, while 2-hop has shown to be optimum for the same type of sensors in battery-powered networks. Also, for sensors with slower dynamics such as body temperature, 1-hop turns out to be optimum in networks solely dependent on energy scavenging while cooperative topology is optimum for battery-powered networks. The algorithm applies to any heterogeneous fully batteryless networks to dynamically optimize packet size at each transmission instance.

Optimization of multiple autonomous underwater vehicle cooperative system communication network topology based on total energy consumption

Given the importance of the communication energy consumption of multiple autonomous underwater vehicle cooperative systems in practical work, this work optimizes the network topology to reduce total energy consumption. In accordance with the characteristics of underwater communication, the energy consumption of communication links is obtained, thereby obtaining the total communication energy consumption of multiple autonomous underwater vehicle cooperative systems. Taking the all-terminal reliability of the communication network as a constraint and the total energy consumption of network communication as the optimization goal, this work puts forward an optimization model for the communication network topology of multiple autonomous underwater vehicle cooperative systems. Furthermore, this work creatively describes the network topology optimization problem as a special path optimization problem suitable for the ant colony optimization algorithm presented to solve the optimization problem and shown to be effective and efficiency on this problem.

Performance Analysis of Bidirectional AF Based Cooperative Vehicular Networks

This paper studies the precise performance of bidirectional amplify and forward (AF) based cooperative vehicular communication networks operating over cascaded Nakagami-m fading environments with arbitrary positive real numbers m, which have been proposed to be a realistically good description of the physical layer channel model of vehicular networks. Exact expressions are derived for four significant performances, namely moment generating function (MGF), higher order moments of signal to noise ratio (SNR), ergodic capacity and average symbol error probability (SEP), whose closed solutions have not been publicly reported. In order to obtain these accurate expressions, we turn our eyes to the MGF of inverse SNR instead of the usual probability density function (PDF) and cumulative distribution function (CDF), which are unknown and difficult to acquire, as well as fail in deriving closed form solutions. Simulation results corroborate the correctness and tightness of the derived expressions, sharp contrast to the approximations and asymptotic values at a sufficiently high SNR region in previous works.

Energy Beamforming for Full-Duplex Wireless Powered Cooperative Communications

In this paper, we consider a full-duplex wireless powered cooperative communication network, where a source communicates with a destination via a decode-and-forward relay in a full-duplex mode. The source and relay harvest energy from the signal transmitted by a power beacon. We formulate an optimization problem to maximize the achievable rate under the transmit power constraint of the power beacon. We find an optimal energy beamforming scheme by solving the optimization problem. Moreover, we obtain a suboptimal solution with lower computational complexity. Simulation results show that the suboptimal scheme suffers little performance degradation compared with the optimal scheme.

Bit error rate performance analysis of AC-MAP in multiple input single output wireless relay network

In this paper, we propose a joint decoding scheme called AC-MAP decoder for multiple input single output (MISO) wireless cooperative communication network that consists of single source, single relay, and single destination. The proposed scheme is based on both Alamouti combining (AC) scheme and maximum a posteriori (MAP) decoder and is used to estimate the data at the destination. The AC-MAP decoder is optimal in the sense that it minimizes the end-to-end bit error rate (BER). In order to analyze performance of the proposed decoder, we derive a closed form expression for the upper bound (UB) on the end-to-end error probability. Distances between system nodes, transmit energy, and channel noise and fading effects are considered in the derivation of the UB. Numerical results show that the closed form UB is very tight and it almost coincides with the exact BER results obtained from simulations. Therefore, we use the derived UB expression to study the effects of the relay position on the BER performance and to find the optimal location of the relay node.

Fair Resource Allocation in Cooperative Cognitive Radio Iot Networks

Due to the growing demand for spectral resources with the emergence of IoT networks and applications, cooperative cognitive radio IoT networks (CCR-IoTN) are expected to play an essential role in the world of smart technology. In this paradigm, the benefits of cooperative communication and cognitive radio networks (CRN) are merged to meet IoT networks' needs. In this work, we employ the hybrid overlay-underlay CRN to guarantee both the secondary user (SU) stability and provide acceptable total throughput. In our CCR-IoTN, SUs may act as a relay to help the primary transmission. If the primary user (PU) is active, the secondary non-relay nodes transmit concurrently with the PU in underlay mode. In return for their cooperation, SUs are allowed to access the spectrum to transmit their data in overlay mode. In this context, we propose several fair resource allocation frameworks and compare well-known problems such as spectrum efficiency, energy efficiency as an objective function for CCR-IoTN. This kind of problem is inherently nonconvex. To solve the problems, therefore, we reformulate them as a convex problem using quadratic transform. Finally, we use simulation to evaluate the performance of the proposed hybrid resource allocation method. The resource allocation framework based on proportional fairness policy is shown to have acceptable performance in terms of throughput, fairness, and energy efficiency.

On UAV Selection and Position-Based Throughput Maximization in Multi-UAV Relaying Networks

Due to flexibility in deployment and high mobility, unmanned aerial vehicles (UAVs) can improve the performance of cellular networks. In this paper, we focus on the UAV-assisted cooperative communication network where multiple UAVs serve as relays between a pair of ground users. Based on signal-to-noise ratio (SNR), we propose two UAV selection strategies namely best harmonic mean (HM) and best downlink SNR (BDS). Then, we derive the closed-form expressions for the outage probability, throughput and coverage probability of both the selection strategies. Furthermore, an optimization problem for maximizing the throughput is formulated, subject to the 3-D coordinates (i.e., x, y, and z coordinates) constraint of the selected UAV. The concavity of the problem is analyzed with respect to the horizontal placement of the selected UAV. Next, we propose algorithms to find optimal and sub-optimal position/coordinates of the selected UAV. Computer simulations validate the accuracy of the derived expressions, and demonstrate that BDS selection strategy has a significant performance gain at low SNR values, whereas both the selection schemes attain a similar performance at high SNRs.

Security Performance Analysis for Best Relay Selection in Energy-Harvesting Cooperative Communication Networks

In this paper, we investigate an energy-harvesting cooperative communication network, which comprises of a source, a destination, and multiple decode-and-forward (DF) relays in the presence of multiple passive eavesdropper (Es). Es attempt to intercept confidential information transmissions from the source to destination via DF relays. In this network, all the DF relays harvest energy from radio-frequency (RF) signals of a source through time-switching receivers. In order to improve the physical layer security of energy-harvesting cooperative communication networks, we propose a best relay selection (BRS) scheme, where the “best” relay is chosen to assist the source-destination transmission. For the purpose of comparison, we consider the classic direct transmission (DT) and equal relay selection (ERS) as benchmark schemes. We derive the exact closed-form expressions of outage probability (OP) and intercept probability (IP) for the ERS and BRS schemes over Rayleigh fading channels. Besides, the security-reliability tradeoff (SRT) is analyzed as a metric to evaluate the tradeoff performance of the proposed BRS scheme. Numerical results show that the SRT of the BRS scheme consistently outperforms that of the ERS scheme, which demonstrates the advantage of our proposed scheme against eavesdroppers. Besides, it is verified that total error rate (TER) defined as the sum of OP and IP can be minimized for both the ERS and BRS schemes through changing the time allocation factor between information transmission and energy harvesting phases. Moreover, there is a best energy conversation efficiency to obtain a maximal SRT value of the ERS and BRS schemes. In addition, as the number of DF relays increases, the SRT of BRS scheme improves notably, while that of ERS scheme remains unchanged. And as the number of Es increases, the SRT of both the ERS and BRS schemes become worse.

Secure Wireless Powered Cooperative Communication Networks With Finite Energy Storage

This paper investigates secure transmission in a wireless powered cooperative communication network (WPCCN) over Nakagami- $m$ fading channels, where multiple intermediate energy harvesting (EH) nodes with finite energy storage are deployed to assist the secure transmission between source and destination in the presence of an eavesdropper. Specifically, the intermediate EH nodes first harvest and accumulate energy from the source's signal and then forward the confidential signal or emit jamming signal to interfere the eavesdropper according to actual requirements. In order to exploit the intermediate EH nodes for secure improvement, considering both energy storage status and channel gains, three relay-and-jammer selection schemes at the intermediate nodes are proposed, namely: energy threshold based best-relay and random-jammer (ETBR), energy threshold based random-relay and best-jammer (ETRB), and energy threshold based best-relay and best-jammer (ETBB). For understanding the impact of critical parameters on the secrecy performance, we first capture the evolution of the EH nodes’ storages using finite-state Markov chain (FSMC) and then derive the analytical expressions for hybrid outage probability (HOP) and secrecy throughput (ST). Furthermore, numerical results demonstrate that our proposed selection schemes outperform the existing schemes (bR-rJ, rR-bJ, bR-bJ) due to the consideration of energy accumulation and storage status. In addition, there is a suitable value of the energy threshold for each proposed scheme to achieve the optimal secrecy performance.

Outage analysis of opportunistic‐based hybrid decode‐amplify‐forward relaying in polar code environment

SummaryOutage analysis plays a vital role in wireless systems to determine reliable transmission and effective communication. Incremental hybrid decode‐amplify‐forward (IHDAF) relay offers a way of meeting the challenges of capacity and coverage improvement with great potential in cooperative communication networks. Therefore, opportunistic incremental hybrid relaying must be integrated with coding schemes to achieve full diversity. In this paper, the outage behavior of polar coded and distributed coded cooperative relaying schemes is analyzed. Simulation results show that opportunistic incremental HDAF using polar code offers an outage capacity of 17 b/s/Hz for 4 × 4 multiantenna and 45 b/s/Hz in 8 × 8 multiantenna systems with an outage of 10−8 and 10−13, respectively. Moreover, the polar coded opportunistic IHDAF system in 8 × 8 MIMO achieves 2 and 6 dB higher gains compared with amplify‐and‐forward (AF) and decode‐and‐forward (DF) relaying schemes. The closed‐form expression for outage probability has been derived through Marcum‐Q approximations and processed through Monte Carlo simulations.

Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network

This paper investigates outage probability (OP) performance predictions using transmit antenna selection (TAS) and derives exact closed-form OP expressions for a TAS scheme. It uses Monte-Carlo simulations to evaluate OP performance and verify the analysis. A back-propagation (BP) neural network-based OP performance prediction algorithm is proposed and compared with extreme learning machine (ELM), locally weighted linear regression (LWLR), support vector machine (SVM), and BP neural network methods. The proposed method was found to have higher OP performance prediction results than the other prediction methods.

Secrecy outage of a multi‐relay cooperative communication network with accumulation of harvesting energy at relays

Security of confidential data at the physical layer has been analysed in a network where the source sends the confidential data to the destination via multiple energy harvesting decode and forward relays in the presence of a single eavesdropper (EAV). In this two-hop communication, the first hop is broadcasting hop when the source sends the information signal to relay and other is the relaying hop when a selected relay forwards the information signal as well as transmits a jamming signal to destination and EAV. Each relay has the two batteries; one for accumulating the harvested energy and the other for power supply to relays for relay operation over a number of frames until the accumulated harvested energy becomes sufficient. In the broadcasting hop, relays harvest energy using a power splitting ratio scheme and accumulate the harvested energy in the battery over a number of communication frames. The performance is analysed in the form of secrecy outage probability (SOP) when the relay uses only the harvested energy to forward the signal. A closed-form analytical expression for the SOP is derived. MATLAB-based simulation results match well with the analytical results.

Integrated Robotic and Network Simulation Method.

The increasing use of mobile cooperative robots in a variety of applications also implies an increasing research effort on cooperative strategies solutions, typically involving communications and control. For such research, simulation is a powerful tool to quickly test algorithms, allowing to do more exhaustive tests before implementation in a real application. However, the transition from an initial simulation environment to a real application may imply substantial rework if early implementation results do not match the ones obtained by simulation, meaning the simulation was not accurate enough. One way to improve accuracy is to incorporate network and control strategies in the same simulation and to use a systematic procedure to assess how different techniques perform. In this paper, we propose a set of procedures called Integrated Robotic and Network Simulation Method (IRoNS Method), which guide developers in building a simulation study for cooperative robots and communication networks applications. We exemplify the use of the improved methodology in a case-study of cooperative control comparison with and without message losses. This case is simulated with the OMNET++/INET framework, using a group of robots in a rendezvous task with topology control. The methodology led to more realistic simulations while improving the results presentation and analysis.

Delay-Optimal Cooperation Policy in a Slotted Aloha Full-Duplex Wireless Network: Static Approach

We consider a cooperative wireless communication network comprising two full-duplex (FD) nodes transmitting to a common destination based on slotted Aloha protocol. Each node has exogenous arrivals and also may relay some of the unsuccessfully transmitted packets of the other node. In this article, we find the optimal static policies of nodes in order to minimize the sum of the average transmission delays, while the average transmission delay of each node is constrained. The static policy of each node specifies the probability of accepting an unsuccessfully transmitted packet of the other node and how the node prioritizes its transmissions. We show that in the optimal policies, just the node with the better link to destination may relay the packets of the other node. We derive optimal acceptance probability of the relaying node in closed form, and show that it should transmit the packets of the other node first. Moreover, we prove that the noncooperation policy is optimal if the ratio of successful transmission rates of nodes does not exceed the Golden ratio. We also show that FD capability of nodes is helpful only when full-acceptance is the optimal policy. Efficiency of the attained optimal policy is illustrated by numerical results.

Outage and Bit Error Probability Analysis in Energy Harvesting Wireless Cooperative Networks

This study focuses on a wireless powered cooperative communication network (WPCCN), which includes a hybrid access point (HAP), a source and a relay. The considered source and relay are installed without embedded energy supply (EES), thus are dependent on energy harvested from signals from the HAP to power their cooperative information transmission (IT). Taking inspiration from this, the author group investigates into a harvest-then-cooperate (HTC) protocol, whereas the source and the relay first harvest the energy from the AP in a downlink (DL) and then collaboratively work in uplink (UL) for IT of the source. For careful evaluation of the system performance, derivations of the approximate closed-form expression of the outage probability (OP) and an average bit error probability (ABER) for the HTC protocol over Rayleigh fading channels are done. Lastly, the author group performs Monte-Carlo simulations to reassure the numerical results they obtained.