Chain store game based channel allocation iu cognitive radio system

In adaptive channel allocation for secondary user (SU) of cognitive radio (CR) system, it is necessary to consider allocation process from the temporal perspective. In this article, a chain store game is modeled to achieve SU's equilibrium state. Due to the computational complexity of solving equilibrium states, the authors explore the correlated equilibrium (CE) by importing signal mechanisms based on time and sequence number. Also, correlated equilibrium based game algorithms are presented. Simulations show that these algorithms are superior to other allocation algorithms both in channel utilization and communication time.     

CR系统中基于博弈论的频谱分配算法及仿真

在分析了无线电频谱管理现状及频谱资源紧张的前提下,引出频谱管理中的认知无线电技术,同时提出了基于博弈论的电磁频谱管理的模型化方法,深入地分析了博弈论算法的收敛性及效用函数的选择,并且通过Matlab仿真以最小化系统间总干扰为目标描述了博弈论模型在电磁频谱动态管理中的应用。     

无线网络中基于图型演化博弈的动态频谱接入机制

无线网络中,为了实现用户高效的数据传输,针对用户的有限理性特性,提出了一种基于图型演化博弈的动态频谱接入机制,而图型博弈可以较好地反映用户之间真实的博弈关系。同时设计了一种动态频谱接入算法和与之对应的动态方程以降低博弈的复杂度,而且能以较快的速度收敛到Nash均衡并获得较高的系统吞吐量和效用。理论证明该动态方程具有全局逐步稳定性,当用户发生局部的理性偏移时依然能够保证较快收敛和较小性能偏离。仿真对比验证了该机制的上述优势。     

Distributed joint spectrum detection and power allocation in multi-band cognitive radio networks

This article proposes a novel dynamic spectrum sharing scheme in distributed multi-band cognitive radio networks. A non-cooperative game has been utilized to model the spectrum sharing among secondary base stations (SBSs). A distributed joint spectrum detection and power allocation algorithm is designed for maximizing the downlink throughput of secondary networks. Simulation results demonstrate that the proposed algorithm converges fast and achieves a better throughput performance than uniform threshold case. Meanwhile, the convergence of algorithm is proved by Nikaido-Isoda (N-I) function method.     

Non‐cooperative power control and spectrum allocation in cognitive radio networks: a game theoretic perspective

The invention of cognitive radio (CR) concept aims to overcome the spectral scarcity issues of emerging radio systems by exploiting under‐utilization of licensed spectrum. Determining how to allocate unused frequency bands among CR is one of the most important problems in CR networks. Because different CRs may have different quality‐of‐service requirements, they may have different objectives. In voice communication, high‐speed transmission is the most important factor; hence, voice radios always try to maximize their transmission rate. However, in data communication, the most important factor is the bit error rate. The data radios always try to maximize their signal‐to‐interference‐plus‐noise ratio (SINR). In this paper, two non‐cooperative games named interference minimization game and capacity maximization game, which reflect the target of data radios and voice radios, respectively, are proposed. From the simulations, after these games are applied, the average SINRs of all players at each channel are improved. The average SINR of players in each channel after applying the capacity maximization game is smaller than that after applying the interference minimization game. However, in comparison with that after applying the interference minimization game, the average capacity of players after applying capacity maximization approach is larger. Copyright © 2012 John Wiley & Sons, Ltd.     

认知小蜂窝网络中基于能效的下行资源分配算法

在认知小蜂窝网络框架下,对基于OFDMA技术的下行联合频谱资源块和功率分配问题进行了研究。小蜂窝基站在分布式结构下采用开放式接入方式共享空闲频谱资源以最大化其能量效率,基站间的竞争关系使系统资源的动态分配过程可建模为非合作博弈模型。由于最大化具有多个限制条件的分数形势的能量效用函数属于非凸最优问题,可通过将其转化为等价的减数形势,并从串行和并行迭代的角度进行求解。在给定资源块分配策略后,原有博弈模型可被重新建模为便于独立求解发射功率的等价子博弈模型。仿真结果表明,所提算法在干扰受限的通信环境下能收敛到纳什均衡,并有效提高了系统资源利用率和能量效率。     

Multi-cell uplink power allocation game for user minimum performance guarantee in OFDMA systems

The multi-cell uplink power allocation problem for orthogonal frequency division multiplexing access (OFDMA) cellular networks is investigated with the uplink transmission power allocation on each co-frequency subchannel being defined as a multi-cell non-cooperative power allocation game (MNPG). The principle of the design oftbe utility function is given and a novel utility function is proposed for MNPG. By using this utility function, the minimum signal to interference plus noise ratio (SINR) requirement of a user can be guaranteed. It can be shown that MNPG will converge to the Nash equilibrium and that this Nash equilibrium is unique. In considering the simulation results, the effect of the algorithm parameters on the system performance is discussed, and the convergence of the MNPG is verified. The performance of MNPG is compared with that of traditional power allocation schemes, the simulation results showing that the proposed algorithm increases the cell-edge user throughput greatly with only a small decrease in cell total throughput; this gives a good tradeoff between the throughput of cell-edge users and the system spectrum efficiency.     

Jointly optimizing sensing time and resource allocation in multichannel cognitive radio networks

Spectrum sensing is a key technique for determining the spectrum available in cognitive radio (CR) networks. In this paper, we study how to jointly optimize sensing time and resource allocation to maximize the sum transmission rate of all CR users of a multichannel CR network. We take into consideration the transmission power and interference constraints to protect primary users from harmful interference, as well as constraints of detection probability and false alarm probability. Under these constraints, we propose an asymptotically optimal resource allocation algorithm. The optimal sensing time can be obtained using the traditional one‐dimensional exhaustive search. However, owing to the high complexity of searching for the sensing time, we propose a simplified method to get the optimal sensing time under the assumption that false alarm probability is small. Simulation results show that the simplified method can obtain the optimal sensing time efficiently under strict constraint of false alarm probability. Copyright © 2012 John Wiley & Sons, Ltd.     

Opportunistic channel allocation decision making in cognitive radio communications

The global spread of wireless devices with mobile Internet access and the increasing demand of multimedia‐based applications are fueling the need for wireless broadband networks. IEEE 802.16 and 802.20 are standards for a broadband wireless access with promising cognitive radio features to support mobile Internet access. However, because of the fast changing radio environment and the demand for dynamic spectrum allocation mechanisms, these standards must continuously readjust different radio parameters. The cognitive radio makes decisions based on its built‐in inference engine, which also in time can adapt itself to different situations through the process of learning from experience. In this paper we present an automated opportunistic decision making and learning process for cognitive radio based on uncertainty reasoning algorithms. This novel approach is well suited in fast changing wireless environments with vague, incomplete, and heterogeneous information. Theory and simulations prove that decision making and learning of the cognitive radio based on the proposed approach cope with the changes in the radio environment. In this work we use fuzzy logic for the learning and decision making of the cognitive radio. Simulation also show that our approach provides accurate and precise decisions on allocating spectrum to mobile Internet users even in fast varying radio conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

基于合作博弈的多信道认知无线网络中的频谱共享算法简

采用合作博弈对多信道认知无线网络中的频谱共享问题进行了建模分析,提出了次用户在各信道上的信干噪比乘积作为合作博弈的效用函数。次用户在各信道上保证对主用户的干扰小于一定门限的要求下,通过最大化各自效用函数的乘积来进行功率分配。由于最大化次用户效用函数的乘积问题是非凸的,通过变量替换将其转化为了一个等价的凸优化问题,利用该凸优化问题的对偶分解,提出了一种次用户间的频谱共享算法。仿真结果表明,所提算法在次用户和速率与公平性之间进行了有效折中。     

Low-complexity joint beamforming and power allocation for SINR balancing in cognitive radio networks

We consider the Signal-to-Interference plus Noise Ratio (SINR) balancing problem involving joint beamfoming and power allocation in the Cognitive Radio (CR) network, wherein the Single-Input Multi-Output Multiple Access Channels (SIMO-MAC) are assumed. Subject to two sets of constraints: the interference temperature constraints of Primary Users (PUs) and the peak power constraints of Cognitive Users (CUs), a low-complexity joint beamforming and power allocation algorithm called Semi-Decoupled Multi-Constraint Power Allocation with Constraints Preselection (SDMCPA-CP) for SINR balancing is proposed. Compared with the existing algorithm, the proposed SDMCPA-CP can reduce the number of matrix inversions and matrix eigen decompositions significantly, especially when large numbers of PUs and CUs are active, while still providing the optimal balanced SINR level for all the CUs.     

基于生存系统模型的认知无线电网络频谱管理自治系统设计

针对动态频谱接入和认知无线电技术对频谱管理的新要求,采用分层的频谱管理理念,基于生存系统模型(Viable System Model,VSM)设计适合认知无线电网络的频谱管理自治系统,该系统通过节点参与频谱管理,网络自我约束等措施,实现认知无线电网络对频谱的自治。最后,将该系统应用于一种异构网络共存的频管案例设计中,仿真分析表明:本文提出的基于VSM的频谱管理自治系统响应时间大幅度降低;认证效率为O(1),较传统方式性能有很大提升。     

Null-space projection and waterfilling resource allocation in multi-antenna cognitive radio networks

Cognitive Radio (CR) is a promising technique for the next generation mobile communication system for its capability to solve the conflicts between the scarcity and underutilization of spectrum. In this paper, aiming at maximizing the system capacity of a multi-antenna CR system on the premise that avoid interference to the primary system in the same band simultaneously, a resource allocation method which is able to avoid interference between PRimary (PR) and CR users by projecting the transmit signals of CR users on the null space of the PR users’ channels is proposed. CR users with better channel condition are selected, and the interference from CR system to PR users can be removed completely by projecting the transmit signals of CR system on the null-space of PR users’ channels. Parallel sub-channels are constructed for CR users through Singular Value Decomposition (SVD). At last, waterfilling is also adopted to increase the CR users’ capacity. Simulation result demonstrates that compared with existing methods, our method can improve the achievable sum rate of CR users as well as reduce the outage probability of PR users.     

Sensing tasks allocation in cellular-based cognitive radio network

In Cognitive Radio (CR) Networks, especially in Cellular-based CR networks, in order to obtain the precise spectrum state which is available in the whole coverage, the spectrum sensing function need to be accomplished by the cooperation of multi-sensing nodes, i.e., cooperative spectrum sensing. This paper mainly focuses on the key question of the cooperative spectrum sensing: How many sensing nodes are required and how to allocate the sensing tasks to these sensing nodes in an effective way? In this paper, we classify the spectrum bands into three categories by a pre-sensing mechanism, in order to firstly exclude unavailable channels and select candidate channels for fine sensing in the next stage. Then the required number of sensing node for each candidate channel is determined by the proposed scheme. Through the scheme proposed in this paper, the sensing tasks allocation in cellular-based CR network can be accomplished in a high effective way and the sensing overhead could keep a low level.     

未知环境中基于图型博弈和Multi-Q学习的动态信道选择算法

研究了分布式无线网络中,没有任何信息交换、也没有环境变化先验知识情况下的动态信道接入算法。运用图型博弈模型对用户的实际拓扑进行建模分析,证明了此博弈模型存在纯策略纳什均衡并且此纳什均衡是全局最优解。同时,采用multi-Q学习求解模型的纯策略纳什均衡解。仿真实验验证了multi-Q学习能获得较高的系统容量以及在图型博弈模型中用户的效用主要由节点的度决定,而与用户数量无直接关系。     

基于非理想感知的认知无线电系统感知时间与频谱分配联合优化算法

针对非理想感知情况下感知时间与频谱分配联合优化问题,同时考虑漏检与主用户重新占用频谱两种场景所造成的主次用户碰撞,并通过量化主用户对认知用户的干扰,给出有无主用户存在时认知系统可获得的吞吐量。在总传输功率约束以及对主用户的最大干扰功率约束两个限制条件下,以最大化系统平均吞吐量为优化目标,给出感知时间与频谱分配联合优化算法。算法首先通过折半法搜索最优感知时间,在既定的感知时间下,将子信道分配给能获得最大平均吞吐量的认知用户,在此基础上,利用凸优化相关理论求得最优功率分配。仿真结果表明,本文所提算法相比于传统频谱分配算法系统平均吞吐量性能提升了10%左右。     

Resource allocation in orthogonal frequency division multiple access‐based cognitive radio systems with minimum rate constraints

In this paper, resource allocation problem in orthogonal frequency division multiple access‐based cognitive radio (CR) systems to maintain minimum transmission rate constraints of CR users (CRUs) with the specified interference thresholds is investigated. Firstly, a single primary user (PU) CR system is considered, and a suboptimal resource allocation algorithm to maximize the sum transmission rate of all CRUs is proposed. Secondly, the single‐PU scenario is extended to multiple‐PU case, and an asymptotically optimal resource allocation algorithm is proposed using dual methods subject to constraints on both interference thresholds of PUs and total transmit power of all CRUs. Analysis and numerical results show that, in contrast to classical resource allocation algorithms, the proposed algorithm can achieve higher transmission rate and guarantee each CRU's minimum transmission rate in both scenarios. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper,we present a non-transferable utility coalition graph game(NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing(OFDMA) based cognitive radio networks to maximize both system throughput and system fairness.In this algorithm,with the assistance of others SUs,SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs.So this scheme can effectively exploit both space and frequency diversity of the system.Performance results show that,NTU-CGG significantly improves system fairness level while not reducing the throughput comparing with other existing algorithms.     

认知无线电频谱分配新算法研究

构造了一个基于合作博奕的非对称纳什协商效能函数,并通过2个认知用户间协商子载波的使用,实现了基于感知贡献加权的比例公平性频谱分配的新算法。仿真结果表明提出的方案不仅实现了频谱资源的公平有效分配,而且有利于频谱感知的最大化。