A Coalitional and Two-Level Game Based Approach for Spectrum Leasing in MIMO Cooperative Cognitive Radio Networks

Wireless Personal Communications - In this work, we studied the resource allocation problem in a spectrum leasing scenario in MIMO cooperative cognitive radio networks (MIMO-CCRN) with multi...     

认知无线电中频谱感知技术的研究进展

认知无线电技术作为解决当前频谱利用率低下这一问题的有效手段,已成为无线电发展的一个新的里程碑。频谱感知作为实现认知无线电的首要任务,主要涉及物理层的信号检测与处理以及链路层的控制与优化。文中对频谱感知技术的最新研究进展情况进行了综述,重点总结和分析了检测算法的性能、协作融合算法以及感知机制的参数优化,并在此基础上讨论了下一步的研究方向。     

Spectrum Sensing Framework for Cognitive Radio Networks

Spectrum sensing feature of cognitive radio devices represents a cornerstone characteristic facilitating real-time and accurate spectrum occupancy measurements in cognitive radio networks. It practically enables the cognitive radio devices to detect vacant spectrum holes and use them for their communication purposes. There are numerous spectrum sensing methods proposed in the literature ranging from local based ones to cooperative strategies among several devices increasing the confidence level of the detected spectrum. This paper gives a general spectrum sensing framework for cognitive radio networks, classifies and explores different spectrum sensing techniques and approaches and shows practical examples, from authors’ own experience, of realized spectrum sensing engines and strategies along with some obtained results.     

认知无线电网络路由及频谱分配联合策略研究

认知无线电网络中的节点可以自主切换通信频率,从而对拓扑和路由产生影响。该文针对多跳认知无线电网络的场景提出了一种路由与频谱分配的联合策略,在按需路由的过程中完成频谱分配任务。实验结果表明,在多数据流并存的认知无线电网络中,该策略较其它路由方法具有更好的适应性和更低的累积时延。     

Distributed Spectrum Sensing Using Radio Environment Maps in Cognitive Radio Networks

Wireless Personal Communications - Ever increasing development of wireless devices and wireless networks have increased the value of spectral space. Many efforts have been conducted to increase...     

认知无线电频谱感知技术综述

针对频谱资源匮乏这一问题,认知无线电技术在提高频谱利用率方面应用前景广泛,而频谱感知作为认知无线电技术实现的前提条件,是目前无线电领域的一个研究热点。近年来人们提出了很多种频谱感知的方法,综述了频谱感知技术的研究进展,对几种典型的传统频谱感知模型进行对比介绍,讨论了几种新型的感知技术,并对各种技术的性能进行深入分析,最后指出了频谱感知研究的挑战及发展趋势。     

A Distributed Message-passing Approach for Clustering Cognitive Radio Networks

Forming collaborative wireless network clusters in dynamically changing environments is essential for cognitive radios to achieve such desired objectives as interference resilience and low communications overhead. In this paper, a novel approach to form efficient node clusters in an ad hoc cognitive radio network (CRN) is introduced based on the affinity propagation (AP) message-passing technique. With this approach, nodes exchange messages containing local network information with their direct neighbours until a high quality set of clusterheads and an efficient cluster structure emerges. The groupings are based on measures of similarity between the network nodes, which are selected based on application requirements. As an initial application, we show how the AP technique can be used to distributively determine cluster assignments and elect a small number of clusterheads that cover a CRN. Such an objective is commonly used to reduce communication overhead in key network functions such as resource management and routing table maintenance. To demonstrate the merits of the proposed approach, the clustering efficiency of the AP technique is evaluated on randomly generated open spectrum access scenarios. The simulation results demonstrate that the proposed approach provides a smaller number of clusters than a standard technique based on approximating the minimum dominating sets of the corresponding ad hoc network graphs.     

A Fittingness Factor-Based Spectrum Management Framework for Cognitive Radio Networks

In order to increase cognitive radios (CRs) operation efficiency, there has been an increasing interest in strengthening awareness level about spectrum utilisation. In this respect, this paper proposes to exploit the fittingness factor concept to capture the suitability of spectral resources exhibiting time-varying characteristics to support a set of heterogeneous CR applications. First, a new knowledge management functional architecture for optimizing spectrum management has been constructed. It integrates a set of advanced statistics capturing the influence of the dynamic radio environment on the fittingness factor. Then, a knowledge manager (KM) exploiting these statistics to monitor time-varying suitability of spectrum resources has been proposed to support the spectrum selection (SS) decision-making process. In particular, a new Fittingness Factor-based strategy combining two SS and spectrum mobility (SM) functionalities has been proposed, following either a greedy or a proactive approach. Results have shown that, with a proper fittingness factor function, the greedy approach efficiently exploits the KM support at low loads and the SM functionality at high loads to introduce significant gains in terms of the user dissatisfaction probability. The proactive approach has been shown to maintain the introduced performance gain while minimizing the signalling requirements in terms of spectrum handover rate.     

非实时业务下认知网络的频谱共享

根据某种特定业务的QoS要求制定相应的频谱共享策略,可以在这种情况下提高系统的频谱利用率,增加用户平均收益。对非实时业务下的认知网络的频谱共享策略进行了研究,考虑各非授权用户业务量和信道质量对系统频谱效率的影响,提出了一种非实时业务专用的NRT-dedicate频谱共享算法。仿真结果表明,在非实时业务情况下,该算法可以获得比通用业务的频谱共享算法的频谱利用率。     

Energy Efficiency-Delay Tradeoffs in CDMA Networks: A Game-Theoretic Approach

A game-theoretic approach for studying energy efficiency-delay tradeoffs in multiple-access networks is proposed. Focusing on the uplink of a code-division multiple-access (CDMA) network, a noncooperative game is considered in which each user seeks to choose a transmit power that maximizes its own utility while satisfying its (transmission) delay requirements. The utility function measures the number of reliable bits transmitted per joule of energy and the user's delay constraint is modeled as an upper bound on the delay outage probability. The Nash equilibrium for the proposed game is derived, and its existence and uniqueness are proved. Using a large-system analysis, explicit expressions for the utilities achieved at equilibrium are obtained for the matched filter, decorrelating and (linear) minimum-mean-square-error (MMSE) multiuser detectors. The effects of delay quality-of-service (QoS) constraints on the users' utilities (in bits per joule) and network capacity (i.e., the maximum number of users that can be supported) are quantified. Using the proposed framework, the tradeoffs between energy efficiency and delay are quantified in a competitive multiuser setting.     

Power Control for Cognitive Radio Networks: A Game Theoretic Approach

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.

     

Blind Spectrum Sensing Algorithms for Cognitive Radio Networks

In a cognitive radio network, the spectrum that is allocated to primary users can be used by secondary users if the spectrum is not being used by the primary user at the current time and location. The only consideration is that the secondary users have to vacate the channel within a certain amount of time whenever the primary user becomes active. Thus, the cognitive radio faces the difficult challenge of detecting (sensing) the presence of the primary user, particularly in a low signal-to-noise ratio region, since the signal of the primary user might be severely attenuated due to multipath and shadowing before reaching the secondary user. In this paper, a blind sensing algorithm is derived, which is based on oversampling the received signal or by employing multiple receive antennas. The proposed method combines linear prediction and QR decomposition of the received signal matrix. Then, two signal statistics are computed from the oversampled received signal. The ratio of these two statistics is an indicator of the presence/absence of the primary signal in the received signal. Our algorithm does not require the knowledge of the signal or of the noise power. Moreover, the proposed detection algorithm in this paper is blind in the sense that it does not require information about the multipath channel distortions the primary signal has undergone on its way to reaching the secondary user. Simulations have shown that our algorithm performs much better than the commonly used energy detector, which usually suffers from the noise uncertainty problem.      

Energy-Efficient Spectrum Discovery for Cognitive Radio Green Networks

Cognitive Radio (CR) is an essential technique for the future generation green communication paradigm owing to its inherent advantages of adaptability and cognition. The compulsory spectrum sensing is a critical component to facilitate systems co-existence. In this paper, we propose a new Time-Division Energy Efficient (TDEE) sensing scheme in which the sensing period is divided into an optimal number of timeslots and each Secondary User (SU) is assigned to detect a different channel in one time-slot. An important advantage of TDEE is that the SUs do not need to exchange the control messages for the acknowledgement of a successful cooperation, leading to substantial energy saving without compromising sensing accuracy. Both homogeneous and heterogeneous networks are investigated with respect to the intrinsic trade-off between spectrum efficiency and energy-efficiency. Illustrative results demonstrate that the proposed TDEE is able to achieve much lower energy consumption and higher throughput, compared to the existing mechanisms.     

基于免疫克隆选择的认知无线网络频谱分配研究

该文提出了图论和免疫优化理论相结合的认知无线网络频谱分配方法。采用基于矩阵的二进制抗体编码,从效率和公平性考虑设计了随机约束满足算子和公平约束满足算子,提出一种基于免疫克隆选择(ICS)的频谱分配算法。对经典克隆选择算法进行改进,增加约束满足操作保证种群编码能够满足频谱干扰限制,实现了频谱分配的约束优化。理论证明了约束满足操作的有效性,分析了算法的计算复杂性和适用性。仿真结果表明：ICS算法与颜色敏感图论着色算法相比,网络带宽明显提高;在频谱干扰严重的情况下,采用公平约束满足算子的ICS算法能显著提高网络的公平性;与参考智能算法相比,ICS算法具有较快的收敛速度。     

认知无线电网络的一种协作频谱感知方案

认知无线电技术能够让非授权用户利用已经分配给授权用户的频段.为了不对首要用户的工作造成干扰,认知用户需要对频谱进行不间断的监测来判断首要用户是否存在.因此,频谱的感知是认知无线电技术的关键.协作频谱感知能够充分的利用网络资源,提高网络中的认知用户的检测概率.文中笔者简单地介绍了一种协作频谱感知的方案.仿真结果表明,通过该方法能够提高网络中认知用户的检测概率,提高网络的检测灵敏度.     

认知网络中的协作频谱感知技术研究

认知无线电技术通过感知频谱后进行动态频谱资源分配,极大地提高了频谱利用效率。频谱感知是实现认知无线电技术的前提和基础,文中针对频谱感知技术中单节点检测的局限性对能够改善频谱感知能力的协作感知技术进行了分析及讨论,重点分析了基于能量检测法的协作感知中的各种数据融合算法,并在此基础上提出了目前协作感知中存在的问题及未来的研究方向。     

Cooperative Spectrum Prediction in Multi-PU Multi-SU Cognitive Radio Networks

Spectrum sensing is considered as the cornerstone of cognitive radio networks (CRNs). However, sensing the wide-band spectrum results in delays and resource wasting. Spectrum prediction, also known as channel status prediction, has been proposed as a promising approach to overcome these shortcomings. Prediction of the channel occupancy, when feasible, provides adequate means for an SU to determine, with a high probability, when to evacuate a channel it currently occupies in anticipation of the PU’s return. Spectrum prediction has great potential to reduce interference with PU activities and significantly enhance spectral efficiency. In this paper, we propose a novel, coalitional game theory based approach to investigate cooperative spectrum prediction in multi-PU multi-SU CRNs. In this approach, cooperative groups, also referred to as coalitions, are formed through a proposed coalition formation algorithm. The novelty of this work, in comparison to existing cooperative sensing approaches, stems from its focus on the more challenging case of multi-PU CRNs and the use of an efficient coalition formation algorithm, centered on the concept of core, to ensure stability. Theoretical analysis is conducted on the upper bound of the coalition size and the stability of the formed coalition structure. A through simulation study is performed to assess the effectiveness of the proposed approach. The simulation results indicate that cooperative spectrum prediction leads to more accurate prediction decisions, in comparison with local spectrum prediction individually performed by SUs. To the best of our knowledge, this work is the first to use coalitional game theory to study cooperative spectrum prediction in CRNs, involving multiple PUs.     

Power Management in MIMO Ad Hoc Networks: A Game-Theoretic Approach

This paper considers interference characterization and management in wireless ad hoc networks using MIMO techniques. The power allocation in each link is built into a non-cooperative game where a utility function is identified and maximized. Due to poor channel conditions, some links have very low data transmission rates even though their transmit powers are high. Therefore, a mechanism for shutting down links is proposed in order to reduce cochannel interference and improve energy efficiency. The multiuser water-filling and the gradient projection methods are compared with the proposed game theoretic approach in terms of system capacity and energy efficiency. It is shown that using the proposed method with the link shut-down mechanism allows the MIMO ad hoc network to achieve the highest energy efficiency and the highest system capacity     

认知无线电网络中合作频谱感知机制的优化

为了提高检测效率和频谱利用率,该文对认知无线电中合作频谱感知的感知机制进行了优化。针对信道监测和信道搜索两个不同的感知场景,分别给出了检测周期、检测时间和搜索时间的选取和优化方法,并提出了新的信道搜索方式。研究分析和仿真结果可以看出,合作频谱感知和主动感知方式的引入可以提高检测性能和传输速率,对感知机制和策略的选取和优化有效地提高系统吞吐量,降低感知时延和开销,这样可以提高认知无线电网络的性能和灵敏性,在保证授权用户不被干扰的同时最大化空闲频谱的接入机会。