Energy harvesting,cooperative spectrum sensing,and data transmission improvement in energy‐efficient multichannel cognitive sensor networks

In this paper, we investigate the energy harvesting capability in a multichannel wireless cognitive sensor networks for energy‐efficient cooperative spectrum sensing and data transmission. Spectrum sensors can cooperatively scan the spectrum for available channels, whereas data sensors transmit data to the fusion center (FC) over those channels. We select the sensing, data transmission, and harvesting sensors by setting the sensing time, data transmission time, and also harvesting time to maximize the network data transmission rate and improve the total energy consumption in the multichannel network under global probability of false alarm and global probability of detection constraints. We formulate our optimization problem and employ the convex optimization method to obtain the optimal times and nodes for spectrum sensing, data transmission, and harvesting energy in each subchannel for multiband cognitive sensor networks. Simulation results show that in our proposed algorithm, the network data transmission rate is improved while more energy is saved compared with the baseline methods with equal sensing time in all subchannels.     

Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory

In this paper, a novel algorithm is proposed for increasing the throughput in cognitive radio networks by forming coalitions among cognitive radio users in AWGN and fading channel environment. Although there have been numerous studies exploring the benefits of coalition formation in cognitive radio networks from the game theory perspective, there are several limitations in their application. To overcome the limitations of game theory, concepts from matching theory are used. Specifically, the stable marriage problem is used to formulate the interactions among the cognitive radio users as a matching game for collaborative distributed spectrum sensing under target detection probability constraint. The utility function is defined as the average probability of false alarm per cognitive radio user. The advantage of stable marriage is that it always converges to a stable matching and is Pareto optimal when the preferences of cognitive radios are strict. In the proposed model, the stable matching problem is extended to propose a novel algorithm to form coalitions of varying sizes for improving the utility of CR (false alarm and throughput). The coalitions formed using the algorithm are stable and do not deviate from the final matching. Using simulations and mathematical analysis, it is shown that the proposed algorithm leads to stable coalitions and returns significant improvement in terms of reduced probability of false alarm and improved throughput per cognitive radio user as compared to the noncooperative scenario.     

感知不确定下卫星认知无线网络多频谱接入优化策略

针对卫星认知无线网络频谱感知不确定性较大导致传统频谱接入机制效率降低的问题,该文提出一种基于动态多频谱感知的信道接入优化策略。认知LEO卫星根据频谱检测概率与授权用户干扰门限之间的关系,实时调整不同频谱感知结果下的信道接入概率。在此基础上以系统吞吐量最大化为目标,设计了一种基于频谱检测概率和虚警概率联合优化的判决门限选取策略,并推导了最佳感知频谱数量。仿真结果表明,认知用户能够在不大于授权用户最大干扰门限的前提下,根据授权信道空闲状态动态选择最佳频谱感知策略,且在检测信号信噪比较低时以更加积极的方式接入授权频谱,降低了频谱感知不确定性对信道接入效率的影响,提高了认知系统吞吐量。     

Throughput optimization using simultaneous sensing and transmission in energy harvesting cognitive radio networks

A three‐dimensional continuous‐time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade‐off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self‐interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works.     

主用户活跃性对新的认知无线电系统容量的影响

在机会频谱接入认知无线电系统中,认知用户只有在通过感知确定信道空闲时才可以接入授权信道,因此频谱感知对于系统性能影响非常重要。本文提出了基于新帧结构的四元频谱感知模型,考虑主用户活跃性对认知网络吞吐量的影响,采用可同时最大化感知和数据传输时间的新帧结构模型,不需要考虑感知和吞吐量的均衡。理论分析新模型下感知时间,主用户活跃性,目标检测概率,主用户接收信噪比对系统吞吐量的影响,并与传统模型进行对比。     

Iterative optimization of detection threshold and throughput for secondary users in multiband cognitive radio systems

In cognitive radio(CR) systems,efficient spectrum sensing ensures the secondary user(SU) to successfully access the spectrum hole.Typically,the detection problem has been considered separately from the optimization of transmission strategy.However,in practice,due to non-zero probabilities of miss detection and false alarm,the sensing phase has an impact on the throughput of SUs as well as on the transmission of primary user(PU).In this paper,using energy detection,we maximize the total throughput of SUs by ...     

基于中继协作的认知无线电性能研究

频谱感知是认知无线电技术的关键。协作频谱感知能够充分利用网络资源,提高网络中认知用户的检测概率,降低认知用户的虚警概率。基于两个认知用户之间的中继协作,研究了协作频谱感知的感知性能与吞吐量的折衷。仿真结果表明：中继协作的频谱感知方法能够使得在充分保证对授权用户不造成干扰即检测概率一定时,能够有效地降低认知用户感知授权用户的虚警概率,缩短＂弱＂认知用户获得最大吞吐量的最优感知时间,提高其最大吞吐量,并提高认知系统的最大吞吐量。     

Coalitional game‐based behavior analysis for spectrum access in cognitive radios

The core of cognitive radio paradigm is to introduce cognitive devices able to opportunistically access the licensed radio bands. The coexistence of licensed and unlicensed users prescribes an effective spectrum hole‐detection and a non‐interfering sharing of those frequencies. Collaborative resource allocation and spectrum information exchange are required but often costly in terms of energy and delay. In this paper, each secondary user (SU) can achieve spectrum sensing and data transmission through a coalitional game‐based mechanism. SUs are called upon to report their sensing results to the elected coalition head, which properly decides on the channel state and the transmitter in each time slot according to a proposed algorithm. The goal of this paper is to provide a more holistic view on the spectrum and enhance the cognitive system performance through SUs behavior analysis. We formulate the problem as a coalitional game in partition form with non‐transferable utility, and we investigate on the impact of both coalition formation and the combining reports costs. We discuss the Nash Equilibrium solution for our coalitional game and propose a distributed strategic learning algorithm to illustrate a concrete case of coalition formation and the SUs competitive and cooperative behaviors inter‐coalitions and intra‐coalitions. We show through simulations that cognitive network performances, the energy consumption and transmission delay, improve evidently with the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

集中式双非参量累积和的合作频谱感知技术

针对认知无线电网络频谱感知的检测时延降低问题，提出了一种采用双非参量累积和的合作频谱感知方法。在单主用户认知网络中，本地认知用户执行非参量累积和算法，处理能量观测数据，以缩短检测时延，减少对主用户先验信息的需求，同时为了降低带宽开销，只向融合中心传输1比特的预判决结果。融合中心在噪声干扰下接收融合预判决结果，执行非参量累积和算法，累加判决统计量，对主用户信号是否存在进行最终判决。仿真结果表明，在10%的虚警概率下，相比于传统的非参量合作频谱感知算法，双非参量累积和算法具有较低的检测延迟。      

频谱异构认知无线电中基于吞吐量降的空时频谱机会感知

在认知无线电(CR)中,频谱感知是实现动态频谱接入的关键技术之一。为适当保护主用户并最大化次级用户的性能,目前大部分相关工作均是用虚报概率和漏检概率作为感知度量来确定最佳感知参数的。但这种度量是用主次用户的碰撞概率来衡量次级用户对主用户的影响的,没有考虑干扰强度的影响,仅适合同构频谱环境;在不同位置次级用户有不同接入机会的异构频谱环境中,并不能最大化频谱利用率。为此,该文首先定义了吞吐量降,并提出在异构频谱环境下采用吞吐量降作为一种新的感知度量。吞吐量降是指由于次级用户占用授权频谱而导致主用户吞吐量下降的百分比。在衡量次级用户对主用户的影响时,它综合了主次用户的碰撞概率和干扰强度两个因素;其次,研究了以吞吐量降为约束的次级用户吞吐量优化问题。最后,数值仿真证实了该方案比目前几种传统方案的频谱利用率显著提高。     

A new sensing‐throughput tradeoff scheme in cooperative multiband cognitive radio network

A conventional cognitive radio network (CRN) uses the spectrum of the licensed primary network (PN) on the premise of detecting the absence of the PN by the spectrum sensing of the sensor node (SN). In this paper, a cooperative multiband CRN is considered, wherein the SNs are allowed to use some time of the transmission slot to relay PN data by cooperative communication, while using the remaining time of the transmission slot to forward its own data, over multiple sub‐bands during each frame, if the presence of PN is detected by cooperative spectrum sensing of the SNs in the sensing slot. A new sensing–throughput tradeoff scheme is formulated as a multi‐variable optimization problem, which maximizes the average aggregate throughput of the CRN over all the sub‐bands by jointly optimizing spectrum sensing time and sub‐band transmission power, subject to the constraints on the average aggregate throughput of the PN, the maximal aggregate power of each SN, and the false alarm and detection probabilities of each sub‐band. The bi‐level optimization method is adopted to obtain the optimal solution by dividing the multi‐variable optimization problem into two convex single‐variable sub‐optimization problems. The simulations show that there exists the optimal sensing time and sub‐band transmission power that maximize the average aggregate throughput of the CRN and, compared with the conventional scheme, the throughput obtained by the proposed scheme is outstanding. Copyright © 2014 John Wiley & Sons, Ltd.     

基于DOA估计的认知无线网络频谱感知

认知无线电技术中频谱感知性能的优劣直接影响认知通信系统的性能。针对该特点提出了认知无线电网络中基于波达方向（ DOA)估计的主用户频谱感知模型,即单主用户多次用户和多主用户多次用户的系统模型,选取基于特征分解的多重信号分类（ MUSIC)算法分析两种模型的感知性能,包括虚警概率、漏检概率、最小总错误概率、算法复杂度等,获得了闭值表达式,最后在两种模型下对算法进行了仿真。仿真结果表明：各参数主要影响虚警概率,而漏检概率几乎不受影响,验证了方法的有效性。     

Adaptively Controlled Cooperative Spectrum Sensing Using OR Fusion Rule for Throughput Maximization in Cognitive Radio

Utilization of wireless spectrum resources should be improved with the great increase of using wireless services. Cognitive radio (CR) has been proposed to overcome the problem of inefficient use of spectrum holes. Spectrum sensing is the most important functional block, which is used to estimate the spectrum holes in the CR system. Cooperative spectrum sensing improves the detection performance and minimizes miss-detection of the primary user. The objective of this paper is to achieve the maximum throughput for all values signal-to-noise ratio (SNR). Cooperative spectrum sensing with fixed sensing time does not provide efficient throughput performance for all values of SNR. In this paper, we propose an adaptively controlled cooperative spectrum sensing scheme using OR fusion rule for throughput maximization in CR system. The proposed scheme estimates the required optimal sensing time for each value of the SNR to achieve the maximum throughput. Simulation results of the proposed scheme demonstrate that it maximizes the achieved throughput for all values of SNR and minimizes the probability of false alarm.

     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

基于部分感知用户协作的多天线频谱检测方案

In this paper, a cooperative spectrum sensing scheme, which is based on cooperation of a certain number of secondary users and cooperative diversity under multi-antenna scenario, is proposed. Under multiantenna scenario, we set a targeted detection probability and optimize the false alarm probability of the network by choosing a certain number of secondary users with the highest primary user’s signal to noise ratio. The detection performance of the network is also evaluated when all the secondary users are cooperating to illustrate the benefits of the proposed scheme as a contrast. In addition, how to choose the detection threshold of the secondary user is analyzed for the purpose of decreasing the average risk. Theory analysis and simulation results show that the optimum false alarm probability can be derived by cooperating a certain number of secondary users rather than all the secondary users and the detection performance of the network can be further improved if secondary users are equipped with multiple antennas. Also, a minimum average risk can be obtained by optimizing the detection threshold.     

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.     

基于协同学习的频谱智能感知方法

目前无线通信网络频谱环境时空分布复杂多变，现有多用户协同感知方法数据预处理繁琐，感知效率低下。为此，在由用户感知层和边缘融合层构成的系统架构下，提出了一种基于协同学习的频谱智能感知算法。用户感知层采用多分支卷积循环门控神经网络，利用原始归一化能量信号的底层结构信息，实现本地感知。边缘融合层基于自注意力机制进行消息传播，融合用户感知层中各个非授权用户的感知结果得出最终决策。实验表明，在信噪比为-20 dB以及5个用户协同感知的情况下，该方法能在虚警概率为1.91%时达到18.3%的检测概率，相比对比模型提升了6.1%,且不需要对原始数据额外预处理，降低了算法的复杂度。     

基于传输中断概率的认知无线电系统性能分析

如何设计最优的频谱感知与传输框架是认知无线电技术的重要环节。考虑频谱接入过程中数据传输中断对认知网络性能影响的问题,提出了一种新的基于传输中断概率的频谱感知与传输模型,联合优化频谱感知和数据传输两个阶段,将问题建模为对主用户的干扰量约束条件下的非凸优问题,以最大化认知网络吞吐量为目标联合优化感知时间、传输速率,并通过数值计算方法对其进行求解与仿真。数值分析表明,引入传输中断概率后,在满足上述约束条件的同时,在保护主用户和认知网络吞吐量、传输时延之间有了更好的权衡。     

衰落信道下的协作频谱检测及其性能分析

在低信噪比和复杂性环境下,协作频谱检测是准确实现频谱感知的有效手段。文中分析了基于能量检测的单用户频谱检测算法以及基于硬判决和等权重的多用户协作频谱检测技术,导出了在高斯信道、Rayleigh衰落信道和Nakagami-m衰落信道情况下协作频谱检测虚警概率和漏检概率的闭合解析式,并对此进行了仿真验证和比较。结果表明,等权重协作频谱检测算法能够有效克服衰落信道对频谱检测的影响。     

A novel approach for energy‐efficient resource allocation in double threshold‐based cognitive radio network

This paper mainly focuses on solving the energy efficiency (EE) maximization problem in double threshold‐based soft decision fusion (SDF) cooperative spectrum sensing (CSS) in the cognitive radio network (CRN). The solution to this objective problem starts with the selection of suitable secondary users (SUs) both for the spectrum sensing and data transmission. Here, energy efficiency is maximized under the constraints of interference to the primary user (PU), an acceptable outage of SUs, the transmission power of the SUs and the probability of false alarm. We propose a novel algorithm called iterative Dinkelbach method (IDM) which jointly optimizes the sensing time and transmission power allocation to the SUs. Further, Lagrangian duality theorem is employed to find the exact power assigned to the SUs. Finally, simulation results are carried out to validate the effectiveness of our proposed scheme by comparing with the other existing schemes. The performance is also analyzed for different system parameters.