Sensing Confidence Level-Based Joint Spectrum and Power Allocation in Cognitive Radio Networks

Cognitive radio (CR) has been extensively investigated in the past decade to tackle the contradiction between wireless spectrum shortage and underutilization. In this paper, we present a unified analytical framework to design PHY-layer spectrum sensing and MAC-layer resource scheduling jointly for CR networks. A key parameter, named sensing confidence level (SCL), is introduced to characterize the presence of imperfect sensing, and bridge the designs between kinds of spectrum sensing schemes and resource allocation algorithms. The SCL-based joint design of spectrum and power allocation is formulated as a mixed integer non-linear optimization problem and Lagrange duality theory is introduced to make the problem tractable. The proposed joint design framework in this paper provides a baseline for comparing different spectrum sensing schemes plus bandwidth and power allocation algorithms. Numerical results demonstrate the effectiveness of the proposed framework.     

非理想信道检测的认知无线电网络中能量感知频谱接入

Due to the problem of spectrum underutilization and energy inefficiency in wireless communications, the research on energy efficient Cognitive Radio Networks (CRNs) has received significant attention in both industry and academia. In this paper, we consider the problem of optimal spectrum selection and transmission parameters design with the objective of minimizing energy consumption in CRNs. Since the system state cannot be directly observed due to miss detections and estimation errors, we formulate the optimal spectrum access problem as a Partially Observable Markov Decision Process (POMDP). In particular, the proposed scheme selects the optimal spectrum, modulation and coding scheme, transmission power, and link layer frame size in each time slot according to the belief state, which captures all the history information of past actions and observations. The optimal policy can be acquired by solving POMDP problem with linear programming based algorithm. Simulation results show that significant energy savings can be achieved by the proposed scheme.     

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.     

Energy-Efficient Power Allocation with Guaranteed QoS Under Imperfect Sensing for OFDM-Based Heterogeneous Cognitive Radio Networks

Wireless Personal Communications - This paper investigates the energy efficient resource allocation scheme for orthogonal frequency division multiplexing based heterogeneous cognitive radio network...     

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.     

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.      

认知无线电的合作频谱检测分析

认知用户需要持续快速地检测主用户的出现,对基于认知无线电的合作频谱检测机制进行了分析。在理想的两用户网络中,认知用户采用合作机制可以提高系统的平均侦测时间。在多认知用户网络中,参与合作的用户越多,单个认知用户对主用户的侦测概率越高。对于多用户网络,还考虑了整体的实现。     

Resource Allocation Algorithm for Multi‐cell Cognitive Radio Networks with Imperfect Spectrum Sensing and Proportional Fairness

This paper addresses the resource allocation (RA) problem in multi‐cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered—such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP‐hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub‐gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.     

Fault-Tolerant Cooperative Spectrum Sensing Scheme for Cognitive Radio Networks

In order to solve the uncertainty resulting from shadowing effect and resist the attack from malicious cognitive radio (CR) users, we propose a fault-tolerant cooperative spectrum sensing scheme for CR networks, where an energy detection-based local spectrum sensing is performed at each CR user, a coefficient is used to weight each CR user’s sensing result, a linear weighted fusion process is performed at the fusion center (FC) to combine received sensing results. For a fault-tolerant cooperative spectrum sensing scheme, the most important issue is to distinguish whether the CR user is reliable or not. In this paper, a reputation-based cooperative mechanism is presented to alleviate the influence of the unreliable sensing results from CR users suffering shadowing and the false sensing data from malicious CR users on the detection result at the FC. In proposed fault-tolerant cooperative scheme, each cooperative CR user has a reputation degree which is initialized and adjusted by the FC and used to weight the sensing result from the corresponding user in the fusion process at the FC. And then, two reputation degree adjusting methods are presented to manage the reputation degree of each CR user. Simulation results show that the proposed scheme can not only weaken the harmful influence caused by malicious CR users, but also alleviate the corrupted detection problem resulting from destructive channel condition between the primary transmitter and the CR user. Moreover, the detection performance of the fault-tolerant cooperative scheme, which has a feasible computational complexity and needs no instantaneous SNRs, is close to that of the optimal scheme.     

Cooperative Spectrum Sensing with Adaptive Node Selection for Cognitive Radio Networks

In cooperative spectrum sensing, secondary users can cooperate based on their local sensing observations so as to detect primary signals in a more reliable manner. However, because of the low strength of received primary signals, observations from some secondary users may contribute little to global decisions at the fusion center. To reduce energy consumption and sensing overhead, cooperation is recommended only with a subset of nodes receiving high-strength primary signals. This paper proposes a selection probability based cooperative spectrum sensing scheme that exploits historical observations to exclude nodes receiving low-strength primary signals. The selection probability is maintained based on local sensing information and global decisions. Simulation results demonstrate that the proposed scheme can exploit location advantages and shows almost the same detection performance as cooperative spectrum sensing with accurate node selection.     

Fast Spectrum Sensing with Coordinate System in Cognitive Radio Networks

Spectrum sensing is an elementary function in cognitive radio designed to monitor the existence of a primary user (PU). To achieve a high rate of detection, most techniques rely on knowledge of prior spectrum patterns, with a trade‐off between high computational complexity and long sensing time. On the other hand, blind techniques ignore pattern matching processes to reduce processing time, but their accuracy degrades greatly at low signal‐to‐noise ratios. To achieve both a high rate of detection and short sensing time, we propose fast spectrum sensing with coordinate system (FSC) — a novel technique that decomposes a spectrum with high complexity into a new coordinate system of salient features and that uses these features in its PU detection process. Not only is the space of a buffer that is used to store information about a PU reduced, but also the sensing process is fast. The performance of FSC is evaluated according to its accuracy and sensing time against six other well‐known conventional techniques through a wireless microphone signal based on the IEEE 802.22 standard. FSC gives the best performance overall.     

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...     

Joint Optimization of Cooperative Spectrum Sensing and Resource Allocation in Multi-channel Cognitive Radio Sensor Networks

Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel instability and noise uncertainty is a promising technique in cognitive radio networks (CRNs). However, the spectrum-sensing parameters which affect the channel-access opportunities of secondary users (SUs) are conventionally regarded as static and treated independently from the resource-allocation strategies. In this paper, joint optimization of CSS, channel access and resource allocation is investigated in an overlay CRN in which each SU carries multi-channel spectrum sensing and transmits the detected energy to a fusion centre in the imperfect reporting channel. An access factor is introduced to describe the channel-access strategies in both cooperative and non-cooperative schemes. Based on the aggregate interference and the transmit power constraints, an optimization problem of multi-channel CSS is formulated to obtain the optimal transmit powers, allocation-access strategies, and sensing threshold of CR system for maximization of the opportunistic throughput. To solve the non-convex problems in both the single and multiple CR systems, the efficient iterative algorithms are developed by exploiting the hidden convexity of the optimization problems. Numerical results show that the performance of our approaches yields a significant enhancement compared with the equal channel-access and equal power-allocation strategy.     

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。     

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。     

Efficient Spectrum Sensing with Minimum Transmission Delay in Cognitive Radio Networks

In cognitive radio (CR) networks, the secondary users (SUs) need to find idle channels via spectrum sensing for their transmission. In this paper, we study the problem of designing the sensing time to minimize the SU transmission delay under the condition of sufficient protection to primary users (PUs). Energy detection sensing scheme is used to prove that the formulated problem indeed has one optimal sensing time which yields the minimum SU transmission delay. Then, we propose a novel cooperative spectrum sensing (CSS) framework, in which one SU’s reporting time can be used for other SUs’ sensing. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, it is proved that there exists one optimal sensing time that minimizes the SU transmission delay. Under hard information fusion, for time varying channels, the novel multi-slot CSS is derived. The performance of SU transmission delay is studied in both perfect and imperfect reporting channels. Some simple algorithms are derived to calculate the optimal sensing settings that minimize the SU transmission delay. Computer simulations show that fundamental improvement of delay performance can be obtained by the optimal sensing settings. In addition, the novel multi-slot CSS scheme shows a much lower transmission delay than CSS based on general frame structure.     

传感能力约束下的认知无线网络的多波段光谱感应优化

This paper addresses the problem of joint optimization of subchannel selection and spectrum sensing time for multiband cognitive radio networks under the sensing capability constrains. In particular, we construct a multiband spectrum sensing framework, and derive the probabilities of detection and false alarm taking the different subchannel gain into account. Furthermore, we formulate the multiband sensing as a two-parameter optimization problem under the sensing capability constrains and guaranteeing the QoS of the secondary user. Moreover, we develop a semi-analytical optimization scheme to achieve the optimal solution.     

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselves to operate in unused bands without disturbing licensed users. The detection capability of a radio system can be enhanced if the sensing process is performed jointly by a group of nodes so that the effects of wireless fading and shadowing can be minimized. However, taking a collaborative approach poses new security threats to the system as nodes can report false sensing data to reach a wrong decision. This paper makes a review of secure cooperative spectrum sensing in cognitive radio networks. The main objective of these protocols is to provide an accurate resolution about the availability of some spectrum channels, ensuring the contribution from incapable users as well as malicious ones is discarded. Issues, advantages and disadvantages of such protocols are investigated and summarized.