WRAN系统中基于自适应内插的信道估计算法

提出了一种基于自适应复系数内插的信道估计算法,改善了无线区域网络（WRAN）系统对抗动态多径时延的能力。WRAN是第一个采用认知无线电技术改善频谱效率的宽带接入标准,系统在下行链路中采用了正交频分复用（OFDM）调制技术,而信道估计技术对于采用相干解调的OFDM系统十分重要。传统的OFDM信道频域响应（CFR）估计算法通常采用实系数频域内插的方式,在对抗WRAN系统长多径时延信道时,不能有效地工作。该文在研究实系数FIR内插变换域响应的基础上,提出了一种复系数内插算法。为了同时适用于短时延信道,提出了一种低复杂度、自适应匹配信道最大多径时延的算法。通过仿真,验证了该算法能够对抗更大的多径时延,提高信道估计的精度,改善系统误码性能。      

Sampling Frequency Offset Estimation for Pilot-Aided OFDM Systems in Mobile Environment

In orthogonal frequency division multiplexing (OFDM) systems, most of the conventional sampling frequency offset (SFO) estimation methods work under the assumption of time-invariant or slow time-variant channels. In mobile environment, the time-variant channel significantly degrades the accuracy of SFO estimation. To solve the problem, we first analyze the properties of time-variant channels. If terminal moves within some tens of the wavelength of radio frequency (RF) signal, channel path delay almost remains unchanged. For most practical OFDM systems, our analysis indicates that channel path delay can be regarded as unchanged during the interval of some tens of OFDM symbols in time-variant channels. Based on the analysis, we propose a novel SFO estimation method for pilot-aided OFDM systems. Different from the conventional methods, the proposed method estimates SFO by detecting the variation of the symbol timing error caused by SFO. The detection is finished by implementing correlation between the channel impulse responses (CIRs) estimated by different OFDM symbols. Performance of the proposed method is simulated and compared with that of two conventional post-FFT methods. Numerical results show that, the proposed SFO estimation method performs better than the conventional methods not only in time-variant channels, but also at low SNRs and large residual carrier frequency offsets (CFOs).     

Data traffic‐based analysis of delay and energy consumption in cognitive radio networks with and without resource reservation

A new opportunistic cross‐layer MAC protocol involving channel allocation and packet scheduling for cognitive radio networks is proposed. Cognitive radio allows secondary users (SUs) to exploit the available portions of the licensed spectrum bands without interfering with primary users. In particular, we consider a cognitive radio system, where SUs are equipped with two transceivers: a control transceiver and a software‐defined radio transceiver. Data traffic characteristics of SUs are considered to ameliorate system performance. So, we propose a mechanism of resource reservation to improve QoS requirements that favors successful SUs to transmit data during x time slots without interfering with primary users. The key novelty of this paper is giving priority for SUs with important data traffic and which frequently solicits data channels to transmit for the remaining time of the ongoing time slot and for the next time slots directly after checking the channel availability. We develop a new analytical model to evaluate delay parameter for two scenarios with and without resource reservation and we then investigate the impact of those scenarios on the energy consumption. We show through simulations that cognitive radio performances increase noticeably with the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

基于OFDM认知无线电网络的最优路径算法

针对基于正交频分复用的分布式认知无线电网络,在考虑频谱移动特性的同时,为保证认知用户数据传输的可靠性,提出一种最优路径的基于OFDM认知无线电网络路由算法.该算法首先通过建立认知无线电网络的模型计算信道的期望传输时间和信道干扰,结合类似于按需路由的基本流程得到所有可能的路径.最后,根据最小累积期望传输时间和路径平均吞吐量的指标来选择最优路径.仿真的结果表明,OROCR算法可以明显地减少平均端到端时延,大大地提高平均端到端吞吐量.     

基于信道分类和自适应调制编码的认知无线电决策引擎

在多径信道条件下,针对单载波频域均衡(SC-FDE)认知系统不能通过多目标优化策略进行决策的问题,该文提出一种基于信道分类和自适应调制编码(AMC)的认知无线电决策引擎。该决策引擎首先对当前信道进行分类,确定当前信道状态;然后根据当前信道状态下的策略切换表选取最优传输策略(MCS),并计算该策略的使用时长(MCSD)。一旦当前策略的持续时间超过了其使用时长,认知决策引擎就会对最优策略进行更新。仿真结果表明,该决策引擎能够提供最优的传输策略以提高频谱效率,使SC-FDE认知系统更好地适应无线信道复杂的电磁环境。     

Symbol Detection of IDMA Systems in the Presence of Carrier Frequency Offsets

In this paper we investigate the detection algorithms for interleave division multiple access (IDMA) systems in the presence of carrier frequency offsets (CFOs). The existing IDMA detection algorithm is designed under the zero CFO assumption and its performance will be degraded when the CFOs are present. We first extend the existing algorithm to the nonzero CFO case by utilizing effective channel coefficients which take the CFO effects into account. Then we turn to a more practical scenario with imperfect CFO estimates. We propose an algorithm that can cope with the residual CFO effects by integrating the CFO updating into the iterative receiver. Signal-to-interference-plus-noise ratio analysis and simulations show the feasibility and superiority of our proposed algorithms.     

An efficient quiet period management scheme for cognitive radio systems

In cognitive radio (CR) systems, the channel sensing scheme for detecting the presence of primary user directly affects the quality-of-service of CR users and primary user. In this letter, we propose a sensing scheme that consists of a series of consecutive energy detections followed by feature detection, where the energy detection time is much shorter than the feature detection time. With the proposed scheme, multiple energy detections decrease the feature detection due to false alarm and the overall channel sensing time. The performance evaluation using Markov analysis shows that the proposed scheme can heighten the maximum channel utilization of CR users, while maintaining the detection delay of primary user under a predefined value.     

On pilot-based multipath channel estimation for uplink CDMA systems: an overloaded case

The paper considers a coding scheme for multipath channel estimation in uplink code-division multiple-access systems where each user transmits an individual pilot signal (sequence) to estimate its multipath channel coefficients. Assuming a common radio channel model with a uniform power delay profile, we derive lower bounds on the maximum mean square error for two types of linear channel estimators: an inverse filter and a linear minimum mean square error (MMSE) estimator. In contrast to previous work, the main focus here is on overloaded systems where the total number of multipath channel coefficients of all users is greater than processing gain. We show that the inverse filter bound is attained if and only if each pilot sequence is a perfect root-of-unity sequence. Interestingly, the conventional matched filter achieves the same lower bound if pilot sequences form a complementary periodic sequence set. In case of the MMSE estimator, the lower bound is either met or not depending on some system parameters. We provide a necessary and sufficient condition for achieving the bound when pilot sequences are arbitrary vectors on the unit sphere. This paper gives insight into the performance limits of practical systems.     

Cognitive radio for next-generation wireless networks: an approach to opportunistic channel selection in ieee 802.11-based wireless mesh - [accepted from open call]

?Cognitive radio? has emerged as a new design paradigm for next-generation wireless networks that aims to increase utilization of the scarce radio spectrum (both licensed and unlicensed). Learning and adaptation are two significant features of a cognitive radio transceiver. Intelligent algorithms are used to learn the surrounding environment, and the knowledge thus obtained is utilized by the transceiver to choose the frequency band (i.e., channel) of transmission as well as transmission parameters to achieve the best performance. In this article we first provide an overview of the different components to achieve adaptability in a cognitive radio transceiver and discuss the related approaches. A survey of the cognitive radio techniques used in the different wireless systems is then presented. To this end, a dynamic opportunistic channel selection scheme based on the cognitive radio concept is presented for an IEEE 802.11-based wireless mesh network.     

Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems

In realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity.     

Joint Semiblind Frequency Offset and Channel Estimation for Multiuser MIMO-OFDM Uplink

A semiblind method is proposed for simultaneously estimating the carrier frequency offsets (CFOs) and channels of an uplink multiuser multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system. By incorporating the CFOs into the transmitted symbols and channels, the MIMO-OFDM with CFO is remodeled into an MIMO-OFDM without CFO. The known blind method for channel estimation (Zeng and Ng in 2004) (Y. H. Zeng and T. S. Ng, ldquoA semi-blind channel estimation method for multi-user multi-antenna OFDM systems,rdquo IEEE Trans. Signal Process., vol. 52, no. 5, pp. 1419-1429, May 2004.) is then directly used for the remodeled system to obtain the shaped channels with an ambiguity matrix. A pilot OFDM block for each user is then exploited to resolve the CFOs and the ambiguity matrix. Two dedicated pilot designs, periodical and consecutive pilots, are discussed. Based on each pilot design and the estimated shaped channels, two methods are proposed to estimate the CFOs. As a result, based on the second-order statistics (SOS) of the received signal and one pilot OFDM block, the CFOs and channels are found simultaneously. Finally, a fast equalization method is given to recover the signals corrupted by the CFOs.     

Artificial bee colony–based spectrum handoff algorithm in wireless cognitive radio networks

In this work, we proposed a new artificial bee colony–based spectrum handoff algorithm for wireless cognitive radio systems. In our wireless cognitive radio system, primary users, secondary users, and related base stations exist in the same communication environment. For our artificial bee colony–based algorithm, secondary users that always struggle to discover an idle channel have a leading role. While honey bees work hard to find the best‐quality nectar source for foraging, secondary users try to find idle channels for making communication. In this way, secondary users are organized for different missions such as sensing and handoff similar to honey bees to minimize spectrum handoff delay by working together. In the spectrum handoff stage, some secondary users must sense the spectrum so that the interrupted secondary user may perform the spectrum handoff process. In our developed spectrum handoff algorithm, the spectrum availability characteristic is observed on the basis of the missions of the bees in the artificial bee colony algorithm with the aim of minimizing the spectrum handoff delay and maximizing probability of finding an idle channel. With the help of the algorithm that is developed using the artificial bee colony, spectrum handoff delay of secondary users is considerably decreased for different number of users without reducing probability of finding an available channel.     

Performance Analysis of Cognitive Radio Multiple-Access Channels Over Dynamic Fading Environments

In dynamically changing environments, the spectrum-sharing method is a promising method to address the spectrum underutilization problem for cognitive radio (CR) systems. This paper investigates the capacity of cognitive radio multiple-access channel (CR-MAC) over a dynamic fading environment. Multiple secondary users (SUs) transmit to the secondary base station under the transmit power (TP) and interference temperature (IT) at the primary base station constraints. In order to perform a general analysis, a theoretical dynamic fading model termed hyper-fading model, which is suitable to the dynamic nature of cognitive radio channel, is considered. The optimal power allocation method is employed to maximize the capacity of CR-MAC for hyper-fading channel with TP and IT constraints and full channel side information. Through the numerical simulations, the capacity of the hyper-fading channels are compared with that of other channel fading models such as Rayleigh, Nakagami-2, and with an additive white Gaussian noise channel. Additionally, the impacts of the number of SUs on capacity is investigated.     

The impact of stochastic resource availability on cognitive network performance: modeling and analysis

Cognitive radio networks emerge as a promising solution for overcoming shortage and inefficient use of bandwidth resources by allowing secondary users (SUs) to access the primary users' (PUs) channel so long as they do not interfere with them. The dynamical spectrum availability makes SU's packet average delay one of the most important performance measures of a cognitive network. It is important to understand the nature of delay, as well as its dependence on PU behaviors. In this paper, we analytically model and analyze the dynamics of the spectrum availability and their impact on the SU's packet delay. The cognitive network is modeled as a discrete‐time queueing system. PU channel occupancy is modeled as a two‐state Markov chain. Our contribution in this paper is defining and characterizing the properties of the random process that describes the availability of the opportunistic resources. In addition, we apply the mean residual service time concept to achieve an analytical solution for the queueing delay. Moreover, inspired by the slotted Aloha system, we model the packet service mechanism and determine the manner in which it depends on the resource availability. The delay becomes unbounded if the spectrum availability dynamics are not carefully considered in network design. Copyright © 2015 John Wiley & Sons, Ltd.     

Joint Estimation of Doubly Selective Channels and Carrier Frequency Offsets in High Mobility MIMO-OFDMA Uplink

In this paper, we address the joint estimation of doubly selective channels (DSCs) and carrier frequency offsets (CFOs) in multiple input multiple output orthogonal frequency division multiple access uplink with highly mobile users. Since the channel coefficients are rapidly varying over time and the base station has to perform the estimation task from the received composite signal, the exact solution to this joint estimation problem requires multidimensional search which is computationally intensive. We propose an iterative technique for the joint estimation of DSCs and CFOs based on space alternating generalized expectation maximization algorithm which will decompose the multidimensional optimization to many one dimensional searches. The proposed method works even in the presence of residual timing offsets and it does not require the knowledge of channel statistics at the receiver. Convergence properties of the proposed algorithm in terms of rate matrix is studied and analytically proved that the proposed joint estimation algorithm converges. Simulation studies illustrate that the proposed technique offers good performance even at very high mobile speeds.

     

A Software Radio Implementation of Centralized MAC Protocol for Cognitive Radio Networks

In the past decade the cognitive radio paradigm has received great attention from academia and industry as a promising approach to solve the spectrum shortage problem. In spite of the intense research activity in the field of cognitive radio, we still register a limited number of network implementations based upon the cognitive radio principles. In this work we present the design and implementation of a proprietary medium access control protocol that we have conjectured using ECMA-392 standard as reference. In the proposed design, the network uses an out-of-band cognitive control channel (CCC) for network management operations. The main contributions of this paper are: (1) a working prototype of a centralized cognitive network implemented in the platform provided by the universal software radio peripheral and GNU Radio software; (2) the presentation of significant data acquired during the field test of our prototype such as average network reconfiguration delay when the CCC is jammed by the primary user and the capability of the cognitive network to reconstruct channel occupancy/vacancy by means of distributed spectrum sensing. The prototype has been designed to operate in the 375–445 MHz frequency bands for a potential application in public safety ad-hoc networks.     

认知无线信道及其可达速率域的研究

认知无线信道是基于认知无线电理论的一种新的无线通信网络模型。到目前为止,已经有一些针对认知无线信道的可达速率域和速率域外界的结果给出,但是还不能得到认知信道的确切的容量域。文中主要研究了认知无线信道模型,以及实现其可达容量域所用到的编码方法,并给出了一些速率域的结果。     

28 GHz MIMO无线信道特性分析与研究

基于室内视距(Line-of-Sight,LOS)和非视距(Non-Line-of-Sight,NLOS)无线信道测量数据,研究了28 GHz多输入多输出(Multiple-Input Multiple-Output,MIMO)信道参数和容量特性.具体地说,分析了莱斯K因子、时延扩展、出发角和到达角的角度扩展等信道参数,研究了MIMO信道容量及空间相关性对容量的影响.结果表明:莱斯K因子、时延扩展以及角度扩展值取决于测量环境及场景;LOS条件下时延扩展的累积分布函数(Cumulative Distribution Function,CDF)曲线与正态分布拟合优于NLOS条件下的数据;MIMO天线空间相关性越大信道容量越小.本文结果可为28 GHz无线通信系统设计提供有用信息.     

Analysis of secondary user performance in cognitive radio networks with reactive spectrum handoff

Cognitive radio networks use dynamic spectrum access of secondary users (SUs) to deal with the problem of radio spectrum scarcity . In this paper, we investigate the SU performance in cognitive radio networks with reactive-decision spectrum handoff. During transmission, a SU may get interrupted several times due to the arrival of primary (licensed) users. After each interruption in the reactive spectrum handoff, the SU performs spectrum sensing to determine an idle channel for retransmission. We develop two continuous-time Markov chain models with and without an absorbing state to study the impact of system parameters such as sensing time and sensing room size on several SU performance measures. These measures include the mean delay of a SU, the variance of the SU delay, the SU interruption probability, the average number of interruptions that a SU experiences, the probability of a SU getting discarded from the system after an interruption and the SU blocking probability upon arrival.