Sidelobe suppression in OFDM-based spectrum sharing systems using adaptive symbol transition

In this letter, we introduce a new method for orthogonal frequency division multiplexing (OFDM) sidelobe suppression. An extension is added to OFDM symbols that is calculated using optimization methods to minimize adjacent channel interference (ACI) while keeping the extension power at an acceptable level. Using this technique, interference to adjacent signals is reduced significantly at the cost of a small decrease in the useful symbol energy. The proposed method can be used by cognitive radio (CR) systems to shape the spectrum of OFDM signals and to minimize interference to licensed users (LU), or to reduce the size of guard bands used in conventional OFDM systems.     

Adaptive subcarrier bandwidth and power in OFDM‐based cognitive radio systems for high mobility applications

OFDM‐based cognitive radio systems are spectrally flexible and efficient, but they are vulnerable to intercarrier interference (ICI), especially in high mobility environments. High mobility of the terminal causes large Doppler frequency spread resulting in serious ICI. Such ICI severely degrades the system performance, which is ignored in the existing resource allocation of OFDM‐based cognitive radio systems. In this paper, an adaptive subcarrier bandwidth along with power allocation problem in OFDM‐based cognitive radio systems for high mobility applications is investigated. This adaptive subcarrier bandwidth method should choose the suitable subcarrier bandwidth not only to balance the tradeoff between ICI and intersymbol interference but also to be large enough to tolerate an amount of Doppler frequency spread but less than the coherence bandwidth. The power budget and interference to primary users caused by cognitive radio users are imposed for primary users' protection. With these constraints, a joint optimization algorithm of subcarrier bandwidth and power allocation is proposed to maximize the bandwidth efficiency of OFDM‐based cognitive radio systems in such conditions. Numerical simulation results show that the proposed algorithm could maximize the system bandwidth efficiency and balance this tradeoff while satisfying the constraints. Copyright © 2012 John Wiley & Sons, Ltd.     

Robust Cognitive‐Radio‐Based OFDM Architecture with Adaptive Traffic Allocation in Time and Frequency

Cognitive radio (CR) has been proposed as an effective technology for flexible use of the radio spectrum. The interference between primary users and CR users, however, becomes a critical problem when they are using adjacent frequency channels with different transmission power levels. In this paper, a robust CR orthogonal frequency division multiplexing (OFDM) architecture, which can effectively suppress interference to nearby primary users and overcome adjacent channel interference (ACI) to the CR user, is proposed. This new approach is characterized by adaptive data repetition for subcarriers under heavy ACI, and adaptive time spreading for subcarriers near the borders of the CR user's spectrum. The data repetition scheme provides extra power gain against the ACI coming from primary users. Time spreading guarantees an acceptable interference level to nearby primary users. By computer simulation, we demonstrate that, under a CR environment, the proposed CR OFDM architecture outperforms conventional OFDM systems in terms of throughput and BER performance.     

Proportional Fair Resource Allocation Based on Chance-Constrained Programming for Cognitive OFDM Network

Proportional fair resource allocation plays a critical role to balance the spectrum efficiency and fairness for cognitive orthogonal frequency division multiplexing (OFDM) network. However, due to the lack of cooperation between cognitive radio (CR) network and primary network, channel state information between CR base station (CRBS) and primary user (PU) could not be estimated precisely. Therefore, the interference of CRBS–PU couldn’t be computed precisely and chance-constrained programming is adopted to formulate the resource allocation problem. In this work, we study the proportional fair resource allocation problem based on chance-constrained programming for cognitive OFDM network. The objective function maximizes the spectral efficiency of cognitive OFDM network over subcarrier and power allocation. The constraint conditions include the interference constraint of PU with the target probability requirement and the proportional fair rate requirement of CR users. In order to solve the above optimization problem, two steps are taken to develop hybrid immune optimization algorithm (HIOA). In the first step, the probabilistic interference constraint condition is transformed as an uncertain function which is computed by a generalized regression neural network (GRNN). In the second step, we combine immune optimization algorithm and GRNN to develop HIOA. Simulation results demonstrate that HIOA yields higher spectral efficiency while the probabilistic interference constraint condition and the proportional fair rate constraint condition could be satisfied very well.     

Optimal Pilot-Based Channel Estimation in Cognitive Radio

Cognitive radio (CR) technology is to assure the better utilization of the spectrum, permitting the non-licensed users to utilize the unused bands provided to the Licensed or primary users, which is made effective through the application of the Orthogonal Frequency Division Multiplexing (OFDM). The effective utilization of the OFDM channels through temporarily allocating the bands to the unlicensed users avoids interference. In order to ensure the reliable spectrum sensing in CR with effective spectral efficiency, the channel estimation (CE) is enabled in the OFDM-based multi-input and multi-output systems. The channel estimation is facilitated through the pilot-based sequential approach for the least square CE in OFDM-based CR. The optimal insertion of the pilots in the input data symbols before transmitting the signal through the fading OFDM channels in CR is made through the proposed rider grey wolf optimization, which is the integration of the grey wolf optimization and rider optimization algorithm. The estimation is done through the least square of the original channel state and the estimated symbols. The experimental analysis is progressed both in Rician and Rayleigh environments with minimal mean square error of 1.28E?06 and bit error rate of 0.000626.

     

Distributed power control algorithm for cognitive radios with primary protection via spectrum sensing under user mobility

Substantial spectrum gains have been demonstrated with the introduction of cognitive radio however; such gains are usually short lived due to the increased level of interference to licensed users of the spectrum. The interference management problem is herein tackled from the transmitter power control perspective so that transmissions by cognitive radio network does not violate the interference threshold levels at the primary users as well as maintain the QoS requirements of cognitive radio users. We model the cognitive radio network for mobile and immobile users and propose algorithms exploiting primary radio environment knowledge (spectrum use), called power control with primary protection via spectrum sensing. The algorithm is briefly introduced for time invariant systems and demonstrated that it has the ability to satisfy tight QoS constraints for cognitive radios as well as meet the interference constraints for licensed users. We, however, further show that such assumption of terminal immobility in the power control algorithm would fail in cases where user mobility is considered, resulting in increased levels of interference to the primary as well as increased outages in cognitive radio network. We model the link gain evolution process as a distance dependent shadow fading process and scale-up the target signal to interference ratio to cope with user mobility. Since mobility driven power control algorithms for cognitive radios have not been investigated before, we therefore, propose a mobility driven power control framework for cognitive radios based on spectrum sensing, which ensures that the interference limit at the primary receiver is unperturbed at all times, while concurrently maintaining the QoS within the cognitive radio network as compared to static user cases. We also corroborate our algorithms with proof of convergence.     

NC-OFDM系统旁瓣抑制中的可变干扰抵消基函数设计

在抑制非连续载波正交频分复用(Non-contiguous Orthogonal Frequency-Division Multiplexing,NC-OFDM)系统旁瓣的方法中,使用固定长度和矩形形状干扰抵消子载波的主动干扰抵消方法(Active Interference Cancellation,AIC)抑制深度不够,而其改进方法扩展AIC (Extended AIC)对数据子载波干扰又太大.本文发现插入在不同频段的干扰抵消子载波对旁瓣抑制的效果不同,并在此基础上提出对干扰抵消子载波按频率分组,不同组的干扰抵消子载波使用不同的长度与波形,从而提高对NC-OFDM信号旁瓣的抑制效果,同时减小了所引入的载波间干扰.仿真结果表明:采用本文提出的可变基函数方案,在达到-60dB的旁瓣抑制深度时,即使采用高阶的64-QAM符号映射(实验条件是误符号率为10^-5),干扰抵消信号对数据子载波造成的载波间干扰也几乎可以忽略.     

Precoding with interference suppression sequence scheme for OFDM-based cognitive radio systems

Orthogonal frequency division multiplexing(OFDM)is considered to be one of the promising schemes for cognitive radios(CR)systems,due to its flexibility in spectrum shaping.However,the traditional way of spectrum-notching failed to suppress out-of-band leakage enough,resulting in interference with licensed users(LUs).A novel spectrum shaping scheme is proposed in this article,where a precoder with interference suppression sequence(ISS)is for the first time introduced for shaping the spectrum of OFDM signals in OFDM-based CR systems.The precoder matrix together with ISS matrix is obtained by minimizing the power of out-of-band interference,which results in the sufficient interference suppression of OFDM signal to LUs.Analysis and simulation results show that the proposed scheme can significantly suppress the interference power to LUs at a little cost of precoding efficiency.Meanwhile,the peak-to-average-power-ratio(PAPR)is invariable and the bit-error-rate(BER)performance over Rayleigh fading channel is improved.     

Compensation schemes and performance analysis of jointly nonlinear amplifier and timing errors for CP-OFDM based cognitive radio networks

The principal objective of cognitive radio (CR) networks is to configure and share dynamically the spectrum resources in order to avoid user interference and congestion. This goal is limited by the effect of errors synchronization between primary and secondary users. In this paper, we study the impact of the asynchronism on the cyclic prefix-based orthogonal frequency division multiplexing modulation (CP-OFDM) including nonlinear HPA model. The considered system includes a reference primary user perfectly synchronized with its reference base station and Nsu interfering secondary users. We provide a new theoretical aspect of interference analysis in the context of the OFDM based CR network. Furthermore, on the basis of this analysis, we derive the accurate expression of bit error rate in the presence of a Rayleigh flat fading channel. Finally, to solve the problems of asynchronism and nonlinearity, a hybrid iterative method of compensation and parallel interference cancellation have been developed based on these two conditions.

     

Signal Processing in Cognitive Radio

Cognitive radio allows for usage of licensed frequency bands by unlicensed users. However, these unlicensed (cognitive) users need to monitor the spectrum continuously to avoid possible interference with the licensed (primary) users. Apart from this, cognitive radio is expected to learn from its surroundings and perform functions that best serve its users. Such an adaptive technology naturally presents unique signal-processing challenges. In this paper, we describe the fundamental signal-processing aspects involved in developing a fully functional cognitive radio network, including spectrum sensing and spectrum sculpting.      

A novel spectrum sharing scheme for cognitive radios

A novel approach, which combines spectrum adaptation and orthogonal frequency division multiplexing (OFDM), is proposed to share the licensed spectrum dynamically for cognitive radio systems. Given spectrum sensing and channel estimation information by the receiver, an improved model due to signal power thresholds is adopted to achieve spectrum adaptation for unlicensed users. In order to efficiently allocate the unlicensed signal power, a dynamic power allocation algorithm is also proposed. Simulation results indicate that the propositional scheme solves the partial interference problem of interference temperature model (ITM) and improves the spectrum utilization.     

认知超宽带无线电波形设计和频谱整形技术

认知超宽带无线电（CUWBR）系统实现的关键问题是当CUWBR感知到频谱空洞时,怎样设计合适的发送波形和频谱整形使其对合法用户造成的干扰最小。针对这一问题,文中简要介绍了CUWBR系统中基于检测与躲避的抗干扰原理,综述了CUWBR抗干扰发送波形设计和频谱整形技术的研究状况和最新进展,并对未来的发展动态进行了分析。解决这一问题能够提高现有频谱的利用率,缓和频谱供需矛盾,对UWB的实用化和CR的实现有积极的推动意义。     

认知无线电动态频谱分配新算法

动态频谱分配技术是认知无线电的一项关键技术,本文针对以OFDM为传输技术的认知无线电系统,提出了固定速率认知用户和变速率认知用户并存情况下的动态频谱分配新算法。本文算法以最小化每比特发射功率为目标,运用最小最大准则与分步求解的方法,对系统目标函数予以简化,在最大公平意义上对认知小区的空闲频谱资源进行动态分配。仿真结果表明,该算法具有较好的公平性,在固定速率用户功率最小化需求和变速率用户吞吐量最大化的需求之间取得了比较好的平衡,适用于两种需求用户并存环境下的认知无线电系统。      

Auction-Based Throughput Maximization in Cognitive Radio Networks Under Interference Constraint

Cognitive radio is an emerging technique to improve the utilization of radio frequency spectrum in wireless communication networks. That is, spectrum efficiency can be increased significantly by giving opportunistic access of the frequency bands to a group of cognitive users to whom the band has not been licensed. In this paper, as a cross layer application (MAC and physical layers) of graph theory, we consider the problem of throughput maximization of spectrum allocation in cognitive radio networks under interference constraint. We propose a novel auction-based channel allocation mechanism which tries to maximize both total and primary users’ utilities while satisfying signal to interference ratio constraint on primary receivers so that transmitted packets will be successfully received, without controlling secondary user powers. For comparison we discuss a greedy algorithm as well, however, one that does not handle interference issue. In order to compare results of proposed and greedy algorithms, we propose net throughput by taking into account outage probability of primary receiver. Simulation results show that exposing higher SINR (outage) threshold not only decreases total gain and primary users’ utilities but also worsens channel distribution performance. On the other hand adding auction mechanism significantly increases total gain throughput and primary user’ s utility. Particularly, up to SINR threshold values of 20 dBs, auction provides outstanding performance and proposed algorithm has total throughput results close to those of the greedy one even though no interference constraint is applied in the greedy algorithm. Another noticeable point of simulation results is crossover of net throughputs of proposed and greedy algorithms at a SINR threshold level after which results of ABSA-UNIC and NASA-UNIC are much better. This clearly shows superiority of proposed mechanism.     

认知无线电中基于Stackelberg博弈的分布式功率分配算法

在underlay认知无线电场景中,为了让认知用户能随机地接入主用户正在使用的授权频段,且对主用户产生的干扰不高于主用户能够容忍的干扰温度门限,该文采用Stackelberg博弈机制进行认知用户的发射功率分配。将主用户作为模型中的leader,认知用户作为follower,认知用户使用主用户的授权频段时需以干扰功率为单位支付给主用户相应的费用,而主用户则可以通过调整价格,限制认知用户产生的总干扰功率不高于其所能容忍的干扰温度门限,以便获得最大收益。同时,不同认知用户间根据主用户制定的价格,进行非协作博弈。仿真结果表明,与集中式的最优功率分配算法相比,该文可通过简单的分布式功率分配算法获得与其相近的系统性能,且主用户与认知用户间只需进行少量的信息交互,这与需进行大量信息交互的集中式最优算法相比,具有较大的优势。     

Optimized Ensemble Classifier Based Network Intrusion Detection System for RPL Based Internet of Things

With the increase in user demand for internet access on move, spectrum resource seems to deplete and leads to spectrum crunch. Recent researches reports that this spectrum crunch is not due to spectrum scarcity but due to spectrum underutilization because of legacy static spectrum allocation of spectrum bands. This spectrum utilization and efficiency can be improved by using Dynamic Spectrum Access (DSA) techniques, which correlate with cognitive radio technology in one way or the other. There are three basic approach of communication for cognitive radio technology: Inter-weaved approach, Underlay approach and Overlay approach. Extensive researches has been proposed so far based on the inter-weaved approach and little or negligible using underlay or overlay approach. Using these modes the cognitive users can coexist with the primary users at same geographic time and location. In this paper simple and unique Adaptive Power Control (APC) technique for underlay approach for cognitive radio mobile network is proposed. This techniques introduces a Power Adaptive Transmission (PAT) metric which overcomes three major issues. Firstly, this proposed techniques work efficiently over highly active licensed networks with marginal increased throughput of 0.2 Mbps. Secondly, APC this technique adapts to the requirement of cognitive user and Lastly, primary user power is monitored, to prevent interference and maintain the Quality of Service (QoS) of primary user. Under simulation testing the proposed APC technique outperforms various other underlay as well hybrid techniques for power control under cognitive radio environment with 11% increase in throughput and 32% decrease in delay using APC.

     

认知无线Ad hoc网络的功率控制

当FCC提出传统电视系统和认知无线电网络频谱共享,以增加频谱的利用率时,主要涉及到的问题之_是来自认知无线电网络的干扰不得影响主用户的QoS。在本文中,考虑由低功耗个人／便携设备组成的认知无线电网络与传统电视系统同时运作的情况。本文在保证主用户和认知用户的QoS的情况下,推导出问题的可行性条件,并提出集中式和分布式两种解决方案,最大限度地提高认知用户的能源效率。并且通过仿真表明该方案的有效性。     

认知OFDM系统旁瓣抑制新方法

针对认知正交频分复用(OFDM)系统带外辐射(OBR)严重问题,在研究基于功率谱密度的主动干扰消除算法(PSD-AIC)模型的基础上,提出了动态PSD-AIC的方法,通过对每一子载波位置OBR的计算,比较选择出OBR取值最小处,作为对消子载波的最优位置,显著改善了系统对OBR的抑制性能(增大约10 dB).对比分析了算法的计算开销,研究了设计参数对OBR的影响,提出了实际应用时的参数选择基准.仿真结果和理论分析表明,动态PSD-AIC方法可以显著减小带外干扰.与PSD-AIC方法相比,旁瓣抑制深度可增加约10 dB;与传统AIC方法相比,只需相似计算量,干扰抑制性能便可明显增加.     

Cognitive Radio Based Multi-User Resource Allocation in Mobile Ad Hoc Networks Using Multi-Carrier CDMA Modulation

In this paper, we propose a cognitive radio based multi-user resource allocation framework for mobile ad hoc networks using multi-carrier DS CDMA modulation over a frequency-selective fading channel. In particular, given preexisting communications in the spectrum where the system is operating, in addition to potential narrow-band interference, a channel sensing and estimation mechanism is provided to obtain information such as subcarrier availability, noise power and channel gain. Given this information, both frequency spectrum and power are allocated to emerging new users (i.e., cognitive radio users), based on a distributed multi-user resource allocation framework, in order to satisfy a target data rate and a power constraint of each cognitive radio user, while attempting to avoid interference to the existing communications as well as to minimize total power consumption of the cognitive radio users.     

认知无线电网络子空间映射频谱共享

针对集中式多用户多天线认知无线电网络,分析了子空间映射能够为认知系统提供的通信机会以及理想信道条件下的空间子信道分配方案。在此基础上,提出了一种基于子空间映射的频谱共享策略。根据认知系统的感知结果,计算可以利用的空间子信道数,通过认知用户接入控制和子空间映射避免或抑制系统间干扰,从而在保证授权用户通信质量的前提下,为认知用户提供通信机会。仿真结果表明,与已有的子空间映射频谱共享方法相比,该策略不仅具有更高的认知系统可达和速率,而且能够为认知系统提供更多通信机会。