无线传感器网络的能耗与频谱资源分布式协同优化研究

With the increasing scarcity of spectrum resources, the single-channel wireless sensor networks have the problem of severe interference and excessive energy consumption. Currently, energy consumption optimization and spectrum resources optimization are usually studied separately. Thus, it is difficult to achieve cooperative optimization of network performance. So, we are intended to build a cooperative optimization model of power control and channel assignment for wireless sensor networks, taking advantage of the energy saving of power control and anti-interference of multi-channel technology, to study the impact of network performance law with the energy consumption and spectrum resources distribution. Firstly, considering the node's interference on the effect of power and channel state, a channel interference model is established to study the interference characteristics of channels with each other. Then, in order to minimize energy consumption and interference, considering load balancing, energy efficiency and anti-interference ability and so on, we are build a cooperative optimization model on power control and channel allocation. And the analysis method of the model is researched based on the potential game theory, to explore the law of the network energy consumption and interference with the power and channel changing. And then, the collaborative optimization algorithm of energy and spectrum resources with low complexity is designed to ensure the full use of the spectrum resources in a low power state. The completion of the project will reveal a law of energy and spectrum resources collaborative optimization, deepen the resource optimization mechanism of wireless sensor network, promote the application and development of wireless sensor network technology.

随着频谱资源日益紧缺，单信道无线传感器网络出现干扰严重、能耗过大的问题。目前，多是将能耗优化和频谱优化分开研究，难以达到网络性能协同优化。为此，本项目拟利用功率控制的节能性和多信道技术的抗干扰性，建立无线传感器网络功率控制与信道分配协同优化模型，研究能耗与频谱资源利用率对网络性能的影响规律。首先，考虑功率和信道状态对节点干扰的影响，建立信道干扰模型，研究信道间的干扰特性；然后，以最小化能耗和干扰为协同优化目标，考虑负载均衡、能量有效性和抗干扰能力等因素，构建功率控制与信道分配协同优化模型，并基于势场博弈理论探究协同优化模型的分析方法，获得功率和信道变化对网络能耗与干扰的影响规律；进而，设计具有低复杂度的能耗与频谱资源协同优化算法，保证网络在低能耗状态下充分利用频谱资源。本项目完成将揭示网络能耗和频谱资源协同优化规律，深化无线传感器网络资源优化机理，促进无线传感器网络技术应用和发展。

无线传感器网络作为物联网的重要组成部分在智慧交通、医疗保健等领域得到广泛应用。随着无线通信技术的发展，频谱资源日益短缺，使得能量受限的无线传感器网络面临因通信干扰过大从而造成能耗大、频谱利用率低等问题。因此，如何减小网络干扰与能耗、提高频谱资源利用率成为目前亟待解决的关键问题。. 为有效解决该问题，本项目首先通过IRIS实验平台，得出了不同功率和信道下信号接收强度、丢包率等性能的变化规律，获得了链路可靠传输条件，从而构建了面向通信可靠与能量均衡的拓扑优化模型。在此基础上，以最小化能耗和干扰为目标，运用博弈论，构建了多性能协同优化的拓扑控制博弈模型MPOGM。进而基于MPOGM模型，结合功率控制与多信道分配技术，建立了基于势场博弈的能耗与频谱资源协同优化博弈模型JPMG。最后为降低算法复杂度，结合最佳回应策略，设计了多性能协同优化的拓扑控制博弈算法MPCOSM和能耗与频谱资源协同优化分布式博弈算法JACIRT，实现能耗与频谱资源的协同控制。. 理论分析证明了所建拓扑模型MPOGM与协同优化模型JPMG存在唯一纳什均衡解，同时拓扑控制算法MPCOSM和能耗与频谱资源协同优化算法JACIRT具有较小的信息复杂度与较快的收敛速度以收敛到纳什均衡，具有较小的算法能耗。实验仿真证明拓扑控制算法MPCOSM具有较小发射功率与通信能耗，有效降低了网络干扰，且所建拓扑具有较高的链路通信质量，提高了网络通信可靠性。然而该算法并未有效提高网络频谱资源利用率，因此针对该问题，构建了能耗与频谱资源协同优化的JACIRT算法。仿真结果表明JACIRT算法不仅具有较低的网络能耗，还具有较高的信道公平性，提高了网络频谱资源利用率，延长了网络生命期。最后利用GAINZ节点进行实测研究，证明了JACIRT算法下的网络具有较好的连通性与链路可靠性，同时具有较小的网络时延。. 本项目所提出的模型与算法揭示了网络能耗和频谱资源协同优化规律，深化了WSN资源优化机理，促进了WSN技术的应用和发展。