一种新的认知无线电非合作功率控制博弈算法

当认知无线电网络以"衬底式"(Underlay)的方式与主用户网络共享频谱时,需要对认知用户进行功率控制,以确保认知用户在不干扰主用户的前提下,公平地共享认知频谱资源。利用博弈分析的方法,设计了一个基于链路增益因子的代价函数,并据此提出了一种新的非合作功率控制博弈算法。仿真结果表明,该算法的均衡结果既改善了用户的帕累托(Pareto)性能,又提高了链路增益较差的用户的吞吐量,实现了网络资源的平等共享。     

多媒体CDMA蜂窝网络上行顽健功率控制算法

研究了同时承载带宽保障业务和尽力而为业务的多媒体CDMA蜂窝网络上行链路顽健功率控制问题.考虑业务突发性、链路增益估计误差以及小区间干扰等因素,通过推导中断概率提出了一种非线性迭代算法.在给定尽力而为业务数据率分配方案的情况下,该非线性迭代算法能够判断是否可以通过功率控制有效地保证带宽保障业务和尽力而为业务的服务质量.在此基础上,分别为支持离散数据率和连续数据率的两类多媒体CDMA蜂窝网络设计了相应的上行链路功率控制算法.最后,通过仿真验证了所提出非线性迭代算法的收敛性,并通过与一种次优功率控制算法进行比较说明了所提出功率控制算法的性能优势.     

基于局部拓扑控制的认知网络路由方法

针对认知网络研究一种融合主、次用户多因素优化的局部拓扑控制和路由方法。该方法综合考虑主用户频谱使用情况以及次用户对主用户干扰影响,预测认知链路的稳定性,结合链路功耗,定义一种联合链路代价,提出链路代价最小的局部认知拓扑控制路由 (LCTCR)算法,优化网络拓扑,并在优化后的拓扑上进行网络路由的选择。算法分析和仿真实验证明,在进行认知网络路径选择时,链路功耗和链路稳定性均为重要参数,需联合优化以保证选择更优的实际路由。     

认知网络中基于中继的频谱资源分配

根据无线认知中继网络上、下行链路子载波的信道特性,研究认知网络的频谱资源分配,提出一种上、下行链路子载波联合优化的分配算法。该算法根据子信道增益差值因子的大小分配下行链路子载波,以源节点和中继节点功率最小化为优化目标配对上行链路子载波,以用户的实时需求分配子载波的比特和功率,有效降低了系统的发射功率,提高了系统吞吐量。仿真结果表明,与启发—集中式和分布式辅助反馈传输功率分配算法比较,该联合优化算法的单位比特功耗降低了1.5~3 dBμW,误比特率性能提高了1个数量级左右。     

一种基于功率控制和潜博弈的动态频谱分配算法

功率控制是感知无线电重配置的重要内容之一。结合功率控制的动态频谱分配策略可以有效提高频谱分配的性能。文章构建了一种潜博弈模型,通过在授权链路保护算法中加入功率控制机制,进一步降低对系统中授权用户和其它感知用户的干扰,提高通信链路的信干噪比,改善分配算法的性能。仿真结果表明算法达到了预期的效果,保证了感知无线电系统可靠通信。     

非线性能量收集认知无线电网络的次用户吞吐量最大化方案

针对一对主用户和M对次用户构成的认知无线电网络（cognitive radio network,CRN），研究了非线性能量收集的认知无线电网络的次用户吞吐量最大化问题。具体来说，对于考虑次用户发射器（secondary transmitter,ST）电路功率的情况，首先将主用户吞吐量需求下的次用户吞吐量最大化（secondarythroughput maximization,STM）问题建模为一个非线性优化问题，然后将它转化成凸优化问题，最后提出一种联合使用黄金分割和二分法的低复杂度算法，获得主用户发射器（primarytransmitter,PT）能量传输和次用户信息传输的最优时间分配以及主用户发射器的最优发射功率。对于忽略次用户发射器电路功率的情况，首先证明次用户吞吐量最大化问题的凸特性，然后设计了一个更高效的算法来求解。仿真结果表明，相比等时间分配方案和链路增益优先级方案，提出的设计算法能显著提升次用户吞吐量。     

用PDI GaAs模块设计光站及光接收机常用方案简介

说明： 1）方案1、方案2在-1 dBm光功率输入情况下，光站输出端口电平可达106dBμV，同时链路中还有8dB左右的增益裕量。     

IoT网络中基于多天线技术的无人机通信传输性能优化

为了提高无人机通信传输性能，研究了在物联网中结合多天线技术对无人机通信的上下行链路功率控制。采用可配置波束宽度和功率的阵列天线，对无人机通信的上行链路和下行链路的传输性能进行分析和优化。对于下行链路，提出一种基于地面传感器设备位置信息的自适应功率分配算法，通过研究地面传感器设备接收性能与无人机发射功率和相对位置之间的关系，分析无人机采用固定功率发射时地面传感器设备获得通信速率与其位置的关系，从而最大化下行链路的传输容量。同时针对实际工程需求，考虑覆盖范围内所有用户的服务质量，提出一种基于地面传感器设备位置的功率预均衡算法，从而获取良好的QoS。对于上行链路，考虑在频谱共享环境下的通信机制，提出一种基于地面传感器设备位置的非合作博弈功率控制方法，根据相对位置和最小通信速率需求设计效用函数，证明纳什均衡的存在性和唯一性。最后，针对提出的上下行链路功率控制优化算法，通过仿真结果验证了其正确性，有效保证了系统的传输性能。     

认知无线电中一种基于干扰温度的功率控制算法

基于干扰温度模型,应将认知无线电网络中认知用户与主用户共享频谱时应满足各自的用户服务质量（QoS）问题转化为有约束的非线性功率控制优化问题。运用迭代算法和拉格朗日相关理论探讨出一种近似最优的功率分配算法。理论分析和仿真表明,该算法既能满足主用户的干扰温度容限,同时又能使认知用户获得很好的信噪干扰比,增大系统的吞吐量。     

大规模MIMO时分双工系统的基站天线互易校准算法

对于采用大规模MIMO技术的时分双工系统,基站天线的互易误差会破坏上下行基带信道互易特性,大幅降低系统下行传输性能。考虑到大规模MIMO技术所带来的基站天线间的耦合效应,该文设计了基于总体最小二乘估计的基站天线互易校准算法,以实现对基站的天线互易误差的补偿。该算法以增加计算复杂度为代价,以及通过增加信道测量样本,克服了上下行信道估计误差对现有天线互易误差校准算法的影响。同时,该文通过瑞利商迭代求解降低了该算法的复杂度。若忽略用户天线互易误差,计算机仿真结果表明,该算法相对于现有的基站天线互易误差校正算法,具有1.8 dB左右的性能增益。若考虑用户天线互易误差,该算法相对于已有的算法,具有随信道估计误差方差减小而增大的增益。     

On the study of cognitive two-way relaying using a denoise-and-forward relay

In this paper, we consider a cognitive cooperative wireless system consisting of two primary users, a cognitive base station (CBS) and a secondary user. A cognitive two-way relaying (CTWR) scheme is proposed, where the secondary user tries to assist the primary users to meet their target quality of service (QoS) by acting as a cognitive two-way relay, when the direct link of the two primary users cannot meet the target QoS. As a return, the primary network shares its transmission time-slot with the secondary user. First, the system outage probabilities of traditional direct transmission and CTWR scheme are analyzed, giving both the exact and approximated expressions. Second, a transmission time-slot splitting algorithm between the primary and secondary users is proposed. Third, the ergodic capacity of the secondary user under the CTWR scheme is examined. Finally, simulation results show that the proposed scheme cannot only help the primary users to meet their target QoS, but also improve the communication opportunities of the secondary user.     

Centralized and distributed power control algorithms for multimedia CDMA networks

We study in this paper both centralized and distributed transmitter power control algorithms for multimedia CDMA networks. In our study, users can have different data rates as well as different quality of service (QoS) requirements characterized by bit energy‐to‐interference ratios. For centralized power control, we derive an optimum power assignment which can be obtained by solving a set of linear equations. For distributed power control (DPC), we study the fully distributed power control (FDPC) algorithm. We modify the FDPC algorithm so that it can be used in a multi‐service environment. We prove that, as long as there are solutions of power levels for all users to meet their QoS requirements, the FDPC algorithm can always find one. A quasi‐centralized power control algorithm with partial link gain measurements is proposed to speed up the process in finding a feasible power set. In the algorithm, a base station measures the link gains for all mobiles connected to it. Numerical results show that quasi‐centralized power control can find a feasible power set much faster than distributed power control. Copyright © 2005 John Wiley & Sons, Ltd.     

CR系统中基于微分博弈的功率控制算法

该文针对认知无线电系统动态性的特点,将微分博弈理论应用在认知无线电系统的功率控制中,建立了功率控制的非合作微分博弈模型,提出了一种基于微分博弈的分布式非合作功率控制算法。该算法在满足认知用户平均功率门限和QoS需求的基础上,实现了分布式动态功率控制,获得了反馈纳什均衡解析解。仿真结果表明,该算法可有效控制各认知用户的发射功率,增加系统吞吐量,提高系统性能。     

认知无线Ad hoc网络的功率控制

当FCC提出传统电视系统和认知无线电网络频谱共享,以增加频谱的利用率时,主要涉及到的问题之_是来自认知无线电网络的干扰不得影响主用户的QoS。在本文中,考虑由低功耗个人／便携设备组成的认知无线电网络与传统电视系统同时运作的情况。本文在保证主用户和认知用户的QoS的情况下,推导出问题的可行性条件,并提出集中式和分布式两种解决方案,最大限度地提高认知用户的能源效率。并且通过仿真表明该方案的有效性。     

Optimal Resource Allocation for Spectrum Sensing Based Cognitive Radio Networks with Statistical QoS Guarantees

Resource allocation under spectrum sensing based dynamic spectrum sharing strategy is a critically important issue for cognitive radio networks (CRNs), because they need to not only satisfy the interference constraint caused to the primary users (PUs), but also meet the quality-of-service (QoS) requirements for the secondary users (SUs). In this paper, we develop the optimal spectrum sensing based resource allocation scheme for the delay QoS constrained CRNs. Specifically, we aim at maximizing the maximum constant arrival rate of the SU that can be supported by the time-varying service process subject to the given statistical delay QoS constraint. In our derived power allocation scheme, not only the average transmit and interference power constraints are considered, but also the impact of the PUs?? transmission to the CRNs and the PUs?? spectrum-occupancy probability are taken into consideration. Moreover, the spectrum sensing errors are also taken into consideration. Simulation results show that, (1) the effective capacity of the secondary link decreases when the statistical delay QoS constraint becomes stringent; (2) given the QoS constraint, the effective capacity of the secondary link varies with the interference power constraint and the SNR of the primary link.     

Distributed power control algorithm for cognitive radios with primary protection via spectrum sensing under user mobility

Substantial spectrum gains have been demonstrated with the introduction of cognitive radio however; such gains are usually short lived due to the increased level of interference to licensed users of the spectrum. The interference management problem is herein tackled from the transmitter power control perspective so that transmissions by cognitive radio network does not violate the interference threshold levels at the primary users as well as maintain the QoS requirements of cognitive radio users. We model the cognitive radio network for mobile and immobile users and propose algorithms exploiting primary radio environment knowledge (spectrum use), called power control with primary protection via spectrum sensing. The algorithm is briefly introduced for time invariant systems and demonstrated that it has the ability to satisfy tight QoS constraints for cognitive radios as well as meet the interference constraints for licensed users. We, however, further show that such assumption of terminal immobility in the power control algorithm would fail in cases where user mobility is considered, resulting in increased levels of interference to the primary as well as increased outages in cognitive radio network. We model the link gain evolution process as a distance dependent shadow fading process and scale-up the target signal to interference ratio to cope with user mobility. Since mobility driven power control algorithms for cognitive radios have not been investigated before, we therefore, propose a mobility driven power control framework for cognitive radios based on spectrum sensing, which ensures that the interference limit at the primary receiver is unperturbed at all times, while concurrently maintaining the QoS within the cognitive radio network as compared to static user cases. We also corroborate our algorithms with proof of convergence.     

认知无线网络基于信号博弈的分布式功率控制算法

针对认知无线网络分布式环境下信道信息不对称导致资源分配冲突的问题,该文提出一种基于信号博弈的分布式功率分配算法。考虑具有竞争关系的次用户在不使用控制信道的情况下,通过信号博弈策略依次选择功率分配策略,达到信道信息共享的目的,能有效避免对主用户正常传输的干扰以及竞争次用户之间功率分配冲突。该文对均衡结果进行分析,仿真结果表明该算法可以有效估计信道增益,次用户的吞吐量相对于已有研究得到明显提升。     

Power Control for Link Quality Protection in Cellular DS-CDMA Networks with Integrated (Packet and Circuit) Services

The problem of admission control in a DS-CDMA network carrying a heterogeneous mix of traffic is addressed. In an interference limited system such as DS-CDMA, admission of a new user impacts the performance of all other users, as well as the system capacity. The admission process is concerned with two factors: (1) maintaining the QoS of active users, (2) allocating bandwidth to new users. We propose a simple power control algorithm and prove that it is optimal in the sense of maintaining active link quality while maximizing free capacity for new admissions. The algorithm scales the powers of active links appropriately to achieve link protection and improved tolerance of the link to new interference from bursty sources. This algorithm can be used to overlay bursty packet data services without compromising QoS of active circuits.     

Robust Power Control for Multiuser Underlay Cognitive Radio Networks Under QoS Constraints and Interference Temperature Constraints

Since the nature of mobility and unreliability in wireless communication system may degrade the communication performance, robustness is one of the main concerns in cognitive radio networks (CRNs). In CRNs, the existing power control algorithms based on the assumption of exact system information may not guarantee the communication requirements due to the parameter uncertainties in real system. In this paper, we propose a robust distributed power control algorithm for underlay CRNs. The novelty in our paper is that we consider all possible parameter uncertainties: channel uncertainty and interference uncertainty. Our objective is to maximize the total throughput of secondary users while channel gain and interference plus noise are uncertain. According to the robust optimization theory, uncertain parameters are modeled by additive uncertainties with bounded errors. Through the worst case principle, we transform the robust power control problem into a deterministic optimization one, which is solved by using Lagrange dual decomposition method. Numerical simulation results show that the proposed algorithm can satisfy the QoS requirements of both secondary users and primary users for all uncertainty realizations.