认知无线电中基于比例公平的资源分配方案  

Resource allocation scheme using proportional fairness for cognitive radio networks

作　　者：周刘纪[1] 刘开华[1] 马永涛[1] 

机构地区：[1]天津大学电子信息工程学院,天津300072

出　　处：《计算机工程与应用》2015年第1期81-88,共8页Computer Engineering and Applications

基　　金：天津市科技支撑计划重点项目(No.09ZCKFGX29200)

摘　　要：在基于OFDM的认知无线电网络中,认知用户采用放大转发(Amplify-and-Forward,AF)协作模式进行数据传输。提出了功率和子载波分配及配对的优化算法,认知用户在子载波上的总发射功率是有限的,同时对授权用户造成的干扰必须低于门限值。采用拉格朗日对偶分解法和次梯度法对功率分配算法进行求解,并对子载波分配及配对算法进行了推导。仿真结果表明,与最大化总速率(maximize-total)公平性和最大化最小速率(maximize-worst)公平性相比,比例公平性(maximize-pro-fair)是一个能够使效率与公平性更加均衡的标准;在低信噪比时,就提高系统传输效率以及资源分配公平度指标而言,该算法依然优于其他三种分配方案。In OFDM-based cognitive radio network, the Amplify-and-Forward（AF） scheme is used by cognitive users as cooperative strategy for data transmission. This paper presents a power and subcarrier allocation and pairing scheme （OFDM-PASA）. It is considered that an interference-limited environment, with a transmit sum-power constraint over all channels as well as an aggregate average interference constraint towards Primary User（PU）. The Lagrange decomposition algorithm and sub-gradient algorithm are used to solve the problem of power allocation, and subcarrier allocation and pairing algorithm is also derived. It is shown by simulation results that proportional faimess （maximize-pro-fair） is a well-balanced criterion between efficiency and fairness compared with maximize-total fairness and maximize-worst fairness. In addition, the proposed new resource allocation and subcarrier pairing strategies can achieve substantial transmission efficiency and fairness for the secondary user over the other methods when the Signal-to-Noise Ratio（SNR） is low.

关 键 词：协作通信 认知无线电 功率和子载波分配 放大转发 公平性 频谱共享 

分 类 号：TN911.2[电子电信—通信与信息系统]