认知OFDM网络资源分配技术研究

发布时间：2018-04-05 17:36

本文选题：认知OFDM网络　切入点：资源分配　出处：《南京理工大学》2017年硕士论文

【摘要】：近年来,随着无线通信技术的迅猛发展,人们对无线服务需求的增长,无线频谱资源日趋紧张。与此同时,目前的无线频谱资源分配常采用静态的方式,导致授权频段内存在大量可用空闲频谱,这导致了频谱资源的严重浪费。认知无线电技术能够通过对环境的感知,不断对内部通信参数加以合理调整,从而保持对环境变化的适应性。正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术是一种特殊的多载波调制技术,它将高速的串行数据流分解成若干并行的子数据流进行传输,能够有效对抗符号间干扰以及无线信道的频率选择性衰落,是第四代移动通信系统(4~(rd) Generation,4G)的核心技术。OFDM技术与认知无线网络有机地结合在一起,形成了认知OFDM网络。本文研究了认知OFDM网络中的资源分配算法,重点研究了 underlay模式的组播网络、overlay模式的单播网络和overlay模式的组播网络的资源分配问题。本文主要工作如下:研究了基于underlay模式的认知OFDM组播网络下行链路传输场景,对基于underlay模式的认知OFDM组播网络中的资源分配问题进行了建模,提出了一种基于Zoutendijk可行方向法的最大化能量效率资源分配算法。该算法不仅能够保证认知用户对最低传输速率需求、授权用户的干扰限制要求,以及认知OFDM网络基站总功率的限制;还能有效提高认知OFDM组播网络的能量效率,改进频谱效率。仿真结果表明,该算法的认知OFDM组播网络的能量效率和频谱效率要高于其它算法的能量效率和频谱效率。研究了基于overlay模式的认知OFDM单播网络上行链路传输场景,对基于overlay模式的认知OFDM单播网络中的资源分配问题进行了建模,提出了一种基于罚函数法的功率最小化资源分配算法。该算法不仅能够保证认知用户最小传输速率需求以及误比特率的要求,还能有效降低系统功率消耗。仿真结果表明,使用该算法的认知OFDM单播网络的消耗总功率要低于使用其它算法的消耗总功率。研究了基于overlay模式的认知OFDM组播网络下行链路传输场景,对基于overlay模式的认知OFDM组播网络中的资源分配问题进行了建模,提出了一种基于和声搜索算法的最大化最小传输速率资源分配算法。该算法不仅能够保证认知OFDM组播网络基站功率限制和误比特率的要求,还能有效提高认知OFDM组播网络中组播组的最小传输速率。仿真结果表明,使用该算法的认知OFDM组播网络的总吞吐量要高于其它算法的总吞吐量。
[Abstract]:In recent years, with the rapid development of wireless communication technology and the increasing demand for wireless services, wireless spectrum resources become increasingly scarce.At the same time, the current allocation of wireless spectrum resources often uses a static way, leading to a large number of available free spectrum in the authorized frequency band, which leads to a serious waste of spectrum resources.Cognitive radio technology can continuously adjust the internal communication parameters through the perception of the environment, so as to maintain the adaptability to environmental changes.Orthogonal Frequency Division Multiplexing (OFDM) is a special multicarrier modulation technique, which decomposes the high-speed serial data stream into several parallel sub-data streams for transmission.It is the core technology of the fourth generation mobile communication system, "Generation 4G", which can effectively counteract intersymbol interference and frequency selective fading of wireless channel. It combines with cognitive wireless network organically and forms a cognitive OFDM network.In this paper, the resource allocation algorithms in cognitive OFDM networks are studied, especially in unicast networks based on underlay mode and unicast networks in overlay mode.The main work of this paper is as follows: the downlink transmission scenario of cognitive OFDM multicast network based on underlay mode is studied, and the resource allocation problem in cognitive OFDM multicast network based on underlay mode is modeled.A maximum energy efficiency resource allocation algorithm based on Zoutendijk feasible direction method is proposed.This algorithm can not only guarantee the minimum transmission rate requirement of cognitive users, the interference limitation requirements of authorized users, and the limit of total power of cognitive OFDM network, but also effectively improve the energy efficiency and spectral efficiency of cognitive OFDM multicast networks.Simulation results show that the energy efficiency and spectral efficiency of the cognitive OFDM multicast network are higher than those of other algorithms.The uplink transmission scenario of cognitive OFDM unicast network based on overlay mode is studied. The resource allocation problem in cognitive OFDM unicast network based on overlay mode is modeled and a power minimization resource allocation algorithm based on penalty function is proposed.This algorithm can not only guarantee the minimum transmission rate and bit error rate requirements of cognitive users, but also reduce the power consumption of the system effectively.Simulation results show that the total power consumption of cognitive OFDM unicast networks using this algorithm is lower than that of other algorithms.The downlink transmission scenario of cognitive OFDM multicast network based on overlay mode is studied, and the resource allocation problem in cognitive OFDM multicast network based on overlay mode is modeled.A maximum minimum transmission rate resource allocation algorithm based on harmonic search algorithm is proposed.This algorithm can not only meet the requirements of power limitation and bit error rate (BER) of cognitive OFDM multicast networks, but also improve the minimum transmission rate of multicast groups in cognitive OFDM multicast networks.Simulation results show that the total throughput of cognitive OFDM multicast networks using this algorithm is higher than that of other algorithms.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.53

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