Optimal Number Of Cooperative Nodes Research Articles

Dynamic Node Management for Energy Optimization in Cognitive Radio Systems

Energy efficiency and spectrum sensing performance are two crucial parameters in cognitive radio networks. Enhancing energy efficiency should not come at the cost of sacrificing spectrum sensing performance. This paper introduces a novel sensing node grouping algorithm to address the challenge of balancing energy efficiency and sensing performance. The proposed algorithm first prioritizes spectrum sensing training for each node and estimates their reliability. Nodes with reliability values exceeding a predefined threshold are selected for cooperative spectrum sensing. The selected nodes are divided into two groups using a staggered grouping approach, ensuring equivalent sensing performance between the groups. The groups alternate in performing spectrum sensing operations, with one group engaging in sensing while the other participates in data transmission or remains idle. The optimal number of cooperative nodes is determined through a greedy algorithm, formulated as a constrained optimization problem. The objective is to maximize energy efficiency subject to a constraint on the error probability, ensuring the highest possible energy efficiency while satisfying the required sensing performance criteria. Experimental results demonstrate that the proposed algorithm effectively maximizes energy efficiency while fulfilling the sensing performance requirements. Compared to traditional algorithms, the dynamic grouping algorithm significantly enhances spectrum sensing performance and improves energy efficiency. The algorithm is adaptable to various network configurations and environmental conditions, addressing the challenges faced by existing solutions. This research contributes to the advancement of cognitive radio networks and their applications in various domains, offering a comprehensive and adaptive solution to optimize energy efficiency and spectrum sensing performance.

Optimal Relay Selection Strategy for Energy-Efficient Cooperative Multi-Hop Image Transmission in Wireless Multimedia Sensor Network

For high-quality picture transmission through smart devices in Mobile Multimedia Sensor Networks (MWMSN), high transmission rates, throughput, and a low Bit Error Rate are necessary. At the same time, energy efficiency is always a big problem for battery-powered smart devices like smartphones and tablets. MWMSN makes extensive use of cooperative communication to realize the benefits of the Multiple-Input-Multiple-Output technology. Energy consumption and routing are major challenges for Cooperative Mobile Multimedia Sensor Networks since each node in the network have mobility. The dynamic nature of MWSNs increases with mobility and the consequence is reflected in the control traffic overhead. To address these challenges, a Cluster-based Cooperative Multi-Hop Optimal Relay Selection (CCORS) strategy was proposed by using velocity, distance, and link quality parameters. The proposed technique determines the link quality for every pair of nodes based on values of signal strength and distance parameters. The relay nodes are chosen based on the highest possible Quality of Service (QoS) value, which is calculated to assure route stability, reliability, and durability. Further, we obtained an optimal number of cooperative nodes in every hop with the objective to minimize end-to-end energy consumption. Finally, simulation results demonstrate the effectiveness of the proposed algorithm compared to other state of art algorithms.

A Study on Energy Consumption Optimization for Cooperative Beamforming in Wireless Sensor Networks

In wireless sensor networks where the volume and energy of nodes are limited by batteries, which are difficult or prohibitively expensive to replace or recharge in the most of its application scenarios, so improving energy efficiency has very important significance.Cooperative beamforming forms virtual antenna arrays by multiple adjacent wireless sensor nodes, which improves the signal strength at the receiver and reduces the energy consumption of the transmitter by multiplexing gain and interference management.In this paper, the problem of energy consumption optimization for cooperative beamforming in wireless sensor networks was studied. First, considering both amplifier energy consumption and circuit energy consumption,energy consumption models for both broadcast phase and cooperative beamforming phase was presented.Then,we propose a two-step optimization to minimize the total energy consumption by optimizing the modulation parameter and the number of cooperative nodes.We simulate the total energy consumption for various transmission distances,modulation parameters , path losses and the number of cooperative nodes.The numerical results show that,for different system parameters, selecting the optimal modulation parameter and the optimal number of cooperative nodes can reduce total energy consumption and improve energy efficiency.

A Cooperative MIMO Framework for Wireless Sensor Networks

We explore the use of cooperative multi-input multi-output (MIMO) communications to prolong the lifetime of a wireless sensor network (WSN). Single-antenna sensor nodes are clustered into virtual antenna arrays that can act as virtual MIMO (VMIMO) nodes. We design a distributed cooperative clustering protocol (CCP), which exploits VMIMO's diversity gain by optimally selecting the cooperating nodes (CNs) within each cluster and balancing their energy consumption. The problem of optimal CN selection at the transmit and receive clusters is formulated as a nonlinear binary program. Aiming at minimizing the imbalance in the residual energy at various nodes, we decompose this problem into two subproblems: finding the optimal number of CNs (ONC) in a cluster and the CN assignment problem. For the ONC problem, we first analyze the energy efficiency of two widely used VMIMO methods: distributed Space Time Block Code (DSTBC) and distributed Vertical-Bell Laboratories-Layered-Space-Time (DVBLAST). Our analysis provides an upper bound on the optimal number of CN nodes, which greatly reduces the computational complexity of the ONC problem. The second subproblem is addressed by assigning CNs based on the residual battery energy. To make CCP scalable to large WSNs, we propose a multihop energy-balanced routing mechanism for clustered WSNs (C-EBR) with a novel cost metric. Finally, we derive sufficient conditions on the intra- and intercluster ranges, under which CCP guarantees connectivity of the intercluster topology. Extensive simulations show that the proposed approach dramatically improves the network lifetime.

Systematic energy-balanced cooperative transmission scheme in wireless sensor networks

Energy efficiency is a critical issue in wireless sensor networks (WSNs). In order to minimize energy consumption and balance energy dissipation throughout the whole network, a systematic energy-balanced cooperative transmission scheme in WSNs is proposed in this paper. This scheme studies energy efficiency in systematic view. For three main steps, namely nodes clustering, data aggregation and cooperative transmission, corresponding measures are put forward to save energy. These measures are well designed and tightly coupled to achieve optimal performance. A half-controlled dynamic clustering method is proposed to avoid concentrated distribution of cluster heads caused by selecting cluster heads randomly and to get high spatial correlation between cluster nodes. Based on clusters built, data aggregation, with the adoption of dynamic data compression, is performed by cluster heads to get better use of data correlation. Cooperative multiple input multiple output (CMIMO) with an energy-balanced cooperative cluster heads selection method is proposed to transmit data to sink node. System model of this scheme is also given in this paper. And simulation results show that, compared with other traditional schemes, the proposed scheme can efficiently distribute the energy dissipation evenly throughout the network and achieve higher energy efficiency, which leads to longer network lifetime span. By adopting orthogonal space time block code (STBC), the optimal number of the cooperative transmission nodes varying with the percentage of cluster heads is also concluded, which can help to improve energy efficiency by choosing the optimal number of cooperative nodes and making the most use of CMIMO.

Capacity and resource allocation of cooperative MIMO in ad hoc networks

Cooperative MIMO (Multiple Input–Multiple Output) allows multiple nodes share their antennas to emulate antenna arrays and transmit or receive cooperatively. It has the ability to increase the capacity for future wireless communication systems and it is particularly suited for ad hoc networks. In this study, based on the transmission procedure of a typical cooperative MIMO system, we first analyze the capacity of single-hop cooperative MIMO systems, and then we derive the optimal resource allocation strategy to maximize the end-to-end capacity in multi-hop cooperative MIMO systems. The study shows three implications. First, only when the intra-cluster channel is better than the inter-cluster channel, cooperative MIMO results in a capacity increment. Second, for a given scenario there is an optimal number of cooperative nodes. For instance, in our study an optimal deployment of three cooperative nodes achieve a capacity increment of 2 bps/Hz when compared with direct transmission. Third, an optimal resource allocation strategy plays a significant role in maximizing end-to-end capacity in multi-hop cooperative MIMO systems. Numerical results show that when optimal resource allocation is applied we achieve more than 20% end-to-end capacity increment in average when compared with an equal resource allocation strategy.