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.     

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.     

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.     

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...     

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.     

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.     

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.     

A Novel Evolutionary-Based Cooperative Spectrum Sensing Mechanism for Cognitive Radio Networks

Cognitive radio (CR) is considered as a feasible intelligent technology for 4G wireless networks or self-organization networks and envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, one of the main concerns is to reliably sense the presence of primary users, to attain protection against harmful interference caused by the potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, genetic algorithm (GA) and particle swarm optimization (PSO) are investigated. An imperialistic competitive algorithm (ICA) is proposed to minimize error detection at the common soft data fusion (SDF) center for structurally centralized cognitive radio network (CRN). By using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed method is compared with other evolutionary algorithms, as well as other conventional deterministic, such as maximal ratio combining- (MRC-), modified deflection coefficient- (MDC-), normal deflection coefficient- (NDC-) based SDF schemes and OR-rule HDF based. MATLAB simulations confirm the superiority of the ICA-based scheme over the PSO-, GA-based and other conventional schemes in terms of detection performance. In addition, the ICA-based scheme also shows promising convergence and time running performance as compared to other iterative-based schemes. This makes ICA an adequate solution to meet real-time requirements.     

A Location Privacy-Preserving Method for Spectrum Sharing in Database-Driven Cognitive Radio Networks

The great attention to cognitive radio networks (CRNs) in recent years, as a revolutionary communication paradigm that aims to solve the problem of spectrum scarcity, prompts serious investigation on security issues of these networks. One important security concern in CRNs is the preservation of users location privacy, which is under the shadow of threat, especially in database-driven CRNs. To this end, in this paper, we propose a Location Privacy Preserving Database-Driven Spectrum-Sharing \((\hbox {L-PDS}^2)\) protocol for sharing the spectrum between PUs and SUs in a database-driven CRN, while protecting location privacy of both primary and secondary users, simultaneously. We also present two specific algorithms as implementations of \(\hbox {L-PDS}^2\) protocol. Our analytical results for the privacy protection capability of \(\hbox {L-PDS}^2\) protocol prove that it provides location privacy preservation with very high probability for users of both networks. Moreover, the simulation results show that the proposed algorithms are efficient in terms of run time.     

A Parallel Repeated Auction for Spectrum Allocation in Distributed Cognitive Radio Networks

Cognitive radio (CR) is applied to solve spectrum scarcity. Although the auction theory and learning algorithm have been discussed in previous works, their combination is not yet researched in the distributed CR networks, where secondary users (SUs) can occupy several channels simultaneously by assuming that one channel can be accessed by at most one SU. A parallel repeated auction scheme is proposed to solve resource allocation in multi-user multi-channel distributed spectrum-overlay CR networks. A novel bid scheme in the light of the first-price sealed auction is designed to balance the system utility and allocation fairness. The proposed auction scheme can be developed based on a learning algorithm and be applied to the scenarios where the cooperation among SUs is unavailable. Under the assumption of limited entry budget, SUs can directly decide whether or not to participate in spectrum auction by comparing the possible bid with access threshold which can be applied into situations that SUs have different transmit power. Theoretical analysis and simulation results show that, compared with original myopic scheme and original genie-aided scheme, the proposed auction scheme can obtain a considerable improvement in efficiency and fairness, especially with adequate available resources.     

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