认知无线网络中信道选择算法研究

研究认知无线网络中认知用户（secondary user,SU）的信道选择策略。在每个信道上,由于主用户（primary user,PU）返回的概率不相同,因此SU需要接入一个成功传输概率最大的信道,以尽量避免与PU发生冲突。提出了一个基于EWA学习的信道选择算法,仿真结果表明,SU通过学习历史信道选择的经验,能自适应地选择可用性最好的信道,从而最小化与PU发生冲突的概率,有效地降低了SU进行信道切换的可能性。     

Distributed and Centralized Schemes for Channel Sensing Order Setting in Multi-user Cognitive Radio Networks

Channel sensing order setting is crucial for efficient channel exploration and exploitation in cognitive radio (CR) networks. This paper investigates the sensing order setting problem in multi-channel multi-user CR networks for both distributed scenario and centralized scenario. As the optimal solution is too complicated, two suboptimal greedy search algorithms with much less computational complexities are proposed. The channel availability, channel achievable rate, multi-user diversity and collisions among CR users are considered comprehensively in our proposed methods. For the distributed scenario, a novel potential function is proposed to represent the relative advantage of a channel used by a user among multi channels and multi users, based on which each user can get its own sensing order. For the centralized scenario, a sensing matrix is obtained by a coordinator for all the users. It is shown that, CR users’ average throughput increases and collision probability decreases with the number of channels due to increased transmission opportunities. The total network throughput increases with the number of user pairs due to multi-user diversity. Simulation results validate the efficacy of the proposed schemes in elevating CR users’ throughput and decreasing the probability of collision, and show the performance improvement of the proposed schemes by comparisons with existing works.     

Uncoordinated rate-division multiple-access scheme for pulsed UWB signals

Popular multiple-access schemes for asynchronous users that access the channel at randomly or pseudorandomly chosen time instances are ALOHA and TH-PPM. To cope with the randomness of these signals can be challenging for a receiver. In this paper, an uncoordinated but deterministic multiple-access scheme is proposed that can eliminate some of these drawbacks. The principle of this scheme is that each user transmits with an individual pulse or packet rate, while the duty cycle of the user signals is kept very low. As the access to the channel is asynchronous, collisions will occur. An analytical expression is derived for the collision probability, which depends on the asynchronism between the users. Design rules are derived that make the collision probability independent of the asynchronism. In practical implementations, deviations from the design values for the user rates will occur, and the length of a data packet is limited; the impact of these aspects on the collision probability is discussed. Simulation of a sensor network scenario without transmit power control shows that the design rules that make the collision probability insensitive to the asynchronism also do this for the bit-error rate (BER). The comparison of simulation results for RDMA with binary antipodal modulation and random TH-PSK, which is related to TH-PPM, yields very similar bit-error rates.     

Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game

We consider dynamic spectrum access among cognitive radios from an adaptive, game theoretic learning perspective. Spectrum-agile cognitive radios compete for channels temporarily vacated by licensed primary users in order to satisfy their own demands while minimizing interference. For both slowly varying primary user activity and slowly varying statistics of ?fast? primary user activity, we apply an adaptive regret based learning procedure which tracks the set of correlated equilibria of the game, treated as a distributed stochastic approximation. This procedure is shown to perform very well compared with other similar adaptive algorithms. We also estimate channel contention for a simple CSMA channel sharing scheme.     

Dynamic Channel Allocation in Wireless Networks Using Adaptive Learning Automata

Single-channel based wireless networks have limited bandwidth and throughput and the bandwidth utilization decreases with increased number of users. To mitigate this problem, simultaneous transmission on multiple channels is considered as an option. In this paper, we propose a distributed dynamic channel allocation scheme using adaptive learning automata for wireless networks whose nodes are equipped with single-radio interfaces. The proposed scheme, Adaptive Pursuit learning automata runs periodically on the nodes, and adaptively finds the suitable channel allocation in order to attain a desired performance. A novel performance index, which takes into account the throughput and the energy consumption, is considered. The proposed learning scheme adapts the probabilities of selecting each channel as a function of the error in the performance index at each step. The extensive simulation results in static and mobile environments provide that the proposed channel allocation schemes in the multiple channel wireless networks significantly improves the throughput, drop rate, energy consumption per packet and fairness index—compared to the 802.11 single-channel, and 802.11 with randomly allocated multiple channels. Also, it was demonstrated that the Adaptive Pursuit Reward-Only (PRO) scheme guarantees updating the probability of the channel selection for all the links—even the links whose current channel allocations do not provide a satisfactory performance—thereby reducing the frequent channel switching of the links that cannot achieve the desired performance.     

Stochastic learning automata‐based channel selection in cognitive radio/dynamic spectrum access for WiMAX networks

This paper proposes a cognitive radio‐based dynamic bandwidth allocation scheme for secondary users in a cluster‐based WiMAX network. It uses a learning automata‐based algorithm to find the optimal transmission channel, while ensuring minimum channel loss and a considerably high signal‐to‐noise ratio, and concurrently minimizing costly channel switching activities when primary users request licensed channels. The objective is to coordinate efficient frequency utilization and frequency reusability in each of the clusters in the network and to make data transmission possible without depleting the spectrum. The proposed scheme subsumes unforeseen channel faults into the channel feedback and decides the optimal channel. The system converges asymptotically to an ?‐optimal solution. Copyright © 2014 John Wiley & Sons, Ltd.     

Error Analysis of Grouped Multilevel Space-Time Trellis Coding with the Combined Application of Massive MIMO and Cognitive Radio

In today’s scenario, demand for error-correcting codes with minimal error constraints for wireless communications. Multilevel coding scheme with trellis codes as component codes provides flexible data transmission rates, coding gain, diversity gain with improved spectral efficiency and low decoding complexity. This paper investigates the potential improvements by using the Multilevel coding scheme with massive Multiple-Input Multiple-Output in Cognitive Radio Networks with trellis codes as component codes. This paper discussed space-time coding with beamforming and antenna grouping according to the channel state information. Multilevel Space-time coding is based on multi-level Quadrature Amplitude Modulation signaling and beamforming to mitigate the effect of primary users for the enactment of secondary users in Cognitive Radio. The primary users provide channels dynamically to the secondary user for an unknown duration. Our transmission use Quadrature Amplitude Modulation based signals, with an adaptive grouping of antenna which weight according to the optimization, which inherently depends upon the resource allocation of the secondary user. The results show that the proposed coded system achieves Bit error rate/Symbol error rate/Frame error rate and Signal to noise ratio varies according to sources sensing time.

     

认知无线电网络中基于主系统有限反馈的频谱共享方案

摘 要：提出一种频谱共享方案,该方案适用于同时存在多个主用户和一对次用户的场景。各主用户依据接收机反馈的有限信道质量信息（CQI, channel quality information）分配发送功率及传输速率。次用户根据偷听到的主系统CQI有限反馈,以适当的功率及速率接入信道。次用户接入信道的行为对各主用户造成一定干扰,以致主系统传输速率遭受一定损失。本文在主系统速率损失约束条件下,研究得出了使次系统吞吐量最大化的次用户发送功率及传输速率最佳分配方案。数值结果表明,对于每个主用户仅需反馈3-4个量化比特,次系统的有效吞吐量就可堪比于主次发射端均拥有主系统链路完整CQI的情况。仿真结果显示,所提出的频谱共享方案能够满足主系统速率损失约束。     

Opportunistic power allocation strategies and fair subcarrier allocation in OFDM-based cognitive radio networks

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user’s QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user’s tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.     

Capacity optimizing channel allocation schemes for multi‐service cellular systems with mobile users

In this paper, we study the blocking and dropping probability of mobile users in the multi‐service cellular systems with mobile users. Based on the idea that different services may require different signal‐to‐interference ratios and different reuse factors, we proposed a channel allocation scheme called channel partitioning to support different services using different reuse factors. Under channel partitioning scheme, the channels in each cell are divided into two or more sets of channels and each set of the channels supports certain service, depending on the required reuse factor of the service. We first apply this channel partitioning with fixed channel allocation scheme called fixed channel partitioning (FCP), where a three‐dimensional Markov chain is developed to analyze the impact of the mobile user. After that a simpler model, which can estimate the numeric result from the closed‐form solution, is presented to make the analysis easier. In order to cater for the traffic variation between services and between cells, a dynamic channel partitioning with flexible channel combination scheme, called FDCP, is proposed to support multiple services. This FDCP tries to minimize the effect of assigned channels on the availability of channels for use in the interfering cells. The analysis and the simulation results show that for equal arrival rate of two services, the proposed FCP and FDCP scheme can provide about 32% and 54% improvement, respectively, in terms of grade of service as compared with conventional FCA scheme using a single reuse factor to support two services for the mobile users. Copyright © 2006 John Wiley & Sons, Ltd.     

Optimization of spectrum utilization in cognitive radio system

In Cognitive Radio (CR) networks, CR user has to detect the spectrum channel periodically to make sure that the channel is idle during data transmission frame in order to avoid the collisions to the primary users. Hence recent research has been focused on the interference avoidance problem. Quality of Service (QoS) requirement of CR user will affect the time of data transmission in each frame. In this paper, in order to solve the interference avoidance and spectrum utilization problems without cooperation among CR users, a new scheme to obtain the optimal duration of data transmission frame is proposed to maximize the spectrum utilization and guarantee the protection to the primary users. The main advantages of our proposed scheme include the followings: (1) QoS requirement of CR user is concerned; (2) p-persistent Media Access Control (MAC) random access is used to avoid the collisions among CR users; (3) CR network system capacity is considered. We develop a Markov chain of the primary spectrum channel states and an exponential distribution of the CR user??s traffic model to analyze the performance of our proposed scheme. Computer simulation shows that there is an optimal data transmission time to maximize the spectrum utilization. However, the regulatory constraint of the collision rate to the primary users has to be satisfied at the expense of spectrum utilization. And also the tradeoff between the spectrum utilization and the capacity of the CR system is taken into account.     

Q学习算法在机会频谱接入信道选择中的应用

针对“先听后传”的机会频谱接入中认知用户的信道选择问题,本文提出了一种基于Q学习的信道选择算法。在非理想感知的条件下,通过建立认知用户的信道选择模型并设计恰当的奖励函数,使智能体能够与未知环境不断交互和学习,进而选择长期累积回报最大的信道接入。在学习过程中,本文引入了Boltzmann实验策略,运用模拟退火思想实现了资源探索与资源利用之间的折衷。仿真结果表明,所提算法能够在未知环境先验知识条件下可以快速选择性能较好的信道接入,有效提高认知用户的接入吞吐量和系统的平均容量。      

Performance Analysis of Cognitive Radio Spectrum Access with Different Primary User Access Schemes

The cognitive access process based on different access schemes of the primary user in the spectrum sharing system of cognitive radio is studied. In the cognitive system with finite user population, the primary users access the licensed channels through random access, real-reservation access, pseudo-reservation access and non-random access. The cognitive users access the licensed channels without interfering the primary users. Their access process is modeled using the three-dimensional continuous Markov model. The performance analysis is presented with variation of the number of cognitive users. It is known from the simulated results that the handoff probability, the blocking probability and the forced termination probability of the cognitive users increase with the increase of the number of cognitive users. It is also found that the random access scheme has the highest handoff probability. And the real-reservation access scheme has the highest blocking probability and forced termination probability. In addition, the non-random access scheme has the maximum channel utilization.     

认知Ad Hoc网络能量有效频谱接入策略

针对认知无线Ad Hoc网络中次用户能量受限问题,提出一种基于能量有效性的机会频谱接入策略。联合考虑信道状态的时变性和次用户的频谱感知准确性,基于部分可观测马尔科夫决策过程（POMDP）建立了一种最大化能量有效性的分析架构,指导次用户选择能效最佳信道,并根据信念状态、信道增益和检测概率,自适应控制传输功率。仿真结果表明,该策略能够有效提高次用户传输的能量有效性,通过对传输功率的有效控制,实现了传输性能和能量开销的有效折中。      

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.     

Algorithms for Dynamic Spectrum Access With Learning for Cognitive Radio

We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperatively tries to exploit vacancies in primary (licensed) channels whose occupancies follow a Markovian evolution. We first consider the scenario where the cognitive users have perfect knowledge of the distribution of the signals they receive from the primary users. For this problem, we obtain a greedy channel selection and access policy that maximizes the instantaneous reward, while satisfying a constraint on the probability of interfering with licensed transmissions. We also derive an analytical universal upper bound on the performance of the optimal policy. Through simulation, we show that our scheme achieves good performance relative to the upper bound and improved performance relative to an existing scheme. We then consider the more practical scenario where the exact distribution of the signal from the primary is unknown. We assume a parametric model for the distribution and develop an algorithm that can learn the true distribution, still guaranteeing the constraint on the interference probability. We show that this algorithm outperforms the naive design that assumes a worst case value for the parameter. We also provide a proof for the convergence of the learning algorithm.      

Performance analysis of multiuser selection diversity in SIMO spectrum sharing systems

In this paper, a performance analysis is presented for user selection schemes in a single‐input multiple‐output spectrum sharing system. In the considered system, multiple secondary users try to use the licensed spectrum of a primary user in an opportunistic manner, in which an interference constraint for the primary user is satisfied. In this paper, we first use 2 conventional user selection schemes for single‐input multiple‐output spectrum sharing system and analyze the system performance for each scheme. We then propose a new user selection scheme that can overcome the limitations of those 2 conventional user selection schemes. As for the performance analysis, the average channel capacity, the outage probability, and the bit error rate performances of the system using the presented user selection schemes are analyzed and mathematical closed‐form expressions for the outage probability are derived. The performances of the system are evaluated using the derived mathematical formulas in different cases. In addition, Monte Carlo simulation results are also provided to show the accuracy and correctness of the performed analysis.     

Performance Evaluation of Cooperative Spectrum Sensing Scheme with Censoring of Cognitive Radios in Rayleigh Fading Channel

In this paper, the performance of cooperative spectrum sensing (CSS) with censoring of cognitive radio (CR) users in Rayleigh fading channel is analyzed. More precisely, CR users which employ energy detectors are censored depending on the quality of radio channels between them and a fusion center (FC). Each CR makes a hard decision about primary user (PU) using energy detection and transmits the information to FC using BPSK signaling if that CR user is selected to transmit. A training based channel estimator is used at the FC to estimate the complex Gaussian fading coefficients characterizing the channels between the CR users and the FC. This channel state information on fading coefficients is used for censoring the CR users. Two fusion rules such as majority logic fusion and maximal ratio combining (MRC) fusion rules are applied at the FC for estimating the performance in terms of probability of missed detection (P_m). We develop a simulation test bed for evaluating the performance of CSS scheme. Probability of missed detection has been evaluated for both perfect and imperfect channel estimation for various probabilities of false alarm (P_f), reporting and sensing channel SNR values.     

Performance analysis of an opportunistic multi‐user cognitive network with multiple primary users

Consider a multi‐user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami‐m fading. The interference channel between the secondary users (SUs) and the primary users is assumed to have Rayleigh fading. A power allocation based on the instantaneous channel state information is derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the moment‐generating function, outage performance, symbol error rate performance, and the ergodic capacity are derived. Numerical results corroborate the derived analytical results. The performance is also studied in the asymptotic regimes, and the generalized diversity gain of this scheduling scheme is derived. It is shown that when the interference channel is deeply faded and the peak transmit power constraint is relaxed, the scheduling scheme achieves full diversity and that increasing the number of primary users does not impact the diversity order. Copyright © 2014 John Wiley & Sons, Ltd.     

Cross-Layer Based Opportunistic MAC Protocols for QoS Provisionings Over Cognitive Radio Wireless Networks

We propose the cross-layer based opportunistic multi-channel medium access control (MAC) protocols, which integrate the spectrum sensing at physical (PHY) layer with the packet scheduling at MAC layer, for the wireless ad hoc networks. Specifically, the MAC protocols enable the secondary users to identify and utilize the leftover frequency spectrum in a way that constrains the level of interference to the primary users. In our proposed protocols, each secondary user is equipped with two transceivers. One transceiver is tuned to the dedicated control channel, while the other is designed specifically as a cognitive radio that can periodically sense and dynamically use the identified un-used channels. To obtain the channel state accurately, we propose two collaborative channel spectrum-sensing policies, namely, the random sensing policy and the negotiation-based sensing policy, to help the MAC protocols detect the availability of leftover channels. Under the random sensing policy, each secondary user just randomly selects one of the channels for sensing. On the other hand, under the negotiation-based sensing policy, different secondary users attempt to select the distinct channels to sense by overhearing the control packets over the control channel. We develop the Markov chain model and the M/G^Y/1-based queueing model to characterize the performance of our proposed multi-channel MAC protocols under the two types of channel-sensing policies for the saturation network and the non-saturation network scenarios, respectively. In the non-saturation network case, we quantitatively identify the tradeoff between the aggregate traffic throughput and the packet transmission delay, which can provide the insightful guidelines to improve the delay-QoS provisionings over cognitive radio wireless networks.