Linear MMSE Channel Estimation for Underlay Cognitive Radio Networks

Channel estimation techniques applied to cognitive radio networks (CRN) are analyzed for simultaneously primary and secondary channel estimations operating in underlay cognitive radio networks (uCRN). A complete base-band transmission including pilot sequence transmission, channel matrix estimation and optimal precoder matrix generation based on imperfect channel estimation are described. Also, the effect of imperfect channel estimation has been studied to provide means of developing techniques to overcome problems while enhancing the MIMO communication performance.

WORST SUBCARRIER AVOIDING WATER-FILLING SUBCARRIER ALLOCATION SCHEME FOR OFDM-BASED CRN

Efficient and reliable subcarrier power joint allocation is served as a promising problem in cognitive OFDM-based Cognitive Radio Networks (CRN). This paper focuses on optimal subcarrier allocation for OFDM-based CRN. We mainly propose subcarrier allocation scheme denoted as Worst Subcarrier Avoiding Water-filling (WSAW), which is based on Rate Adaptive (RA) criterion and three constraints are considered in CRN. The algorithm divides the assignment procedure into two phases. The first phase is an initial subcarrier allocation based on the idea of avoiding selecting the worst subcarrier in order to maximize the transmission rate; while the second phase is an iterative adjustment process which is realized by swapping pairs of subcarriers between arbitrary users. The proposed scheme could assign subcarriers in accordance with channel coherence time. Hence, real time subcarrier allocation could be implemented. Simulation results show that, comparing with the similar existing algorithms, the proposed scheme could achieve larger capacity and a near-optimal BER performance.

Cross Layer QoS Aware Scheduling based on Loss-Based Proportional Fairness with Multihop CRN

As huge users are involved,there is a difficulty in spectrum allocation and scheduling in Cognitive Radio Networks(CRNs).Collision increases when there is no allocation of spectrum and these results in huge drop rate and network performance degradation.To solve these problems and allocate appropriate spectrum,a novel method is introduced termed as Quality of Service(QoS)Improvement Proper Scheduling(QIPS).The major contribution of the work is to design a new cross layer QoS Aware Scheduling based on Loss-based Proportional Fairness with Multihop(QoSAS-LBPFM).In Medium Access Control(MAC)multi-channel network environment mobile nodes practice concurrent broadcast between several channels.Acquiring the advantage of introduced cross layer design,the real-time channel conditions offered by Cognitive Radio(CR)function allows adaptive sub channel choice for every broadcast.To optimize the resources of network,the LBPFM adaptively plans the radio resources for allocating to diverse services without lessening the quality of service.Results obtained from simulation proved that QoSAS-LBPFM provides enhanced QoS guaranteed performance against other existing QIPS algorithm.

Optimized in-band control channel with channel selection scheduling and network coding in distributed cognitive radio networks

This article proposes an optimized in-band control channel scheme with channel selection scheduling algorithm and network coding based transmission paradigm in the distributed cognitive radio network （CRN）. As well known, control channel plays an important role for establishment of wireless transmission. In order to improve spectrum efficiency in CRN, control channel is preferred to be deployed without dedicated spectrum allocation, i.e. the in-band way. In this study, the time slot division and dynamic channel selection scheduling algorithm is proposed to realize the in-band control channel with improved spectrum efficiency in the distributed CRN. Furthermore, to adapt to dynamic behavior of the primary users, network coding technology is employed to optimize the overhead of control information transmission so that the control information can be efficiently and reliably transmitted. The performance of the proposed in-band control channel scheme is verified by the extensive simulation results.

Optimal energy-efficiency capacity and sensing tradeoff for hybrid spectrum sharing in CRN

This paper investigates the tradeoff between energy-efficiency capacity and spectrum sensing under hybrid spectrum sharing model, where the spectrum sharing method is based on sensing results of secondary user （SU）. The metric ＇bits per joule＇, which captures the effect of energy overhead in spectrum sensing, is adopted to evaluate energy-efficiency capacity. We first formulize the tradeoff between energy-efficiency capacity and spectrum sensing as an optimization problem with mixture constraint of sensing time and detection threshold. Under some certain condition on the domain of detection threshold, i.e. in which we can＇t improve energy-efficiency capacity through increasing the detection probability, the original optimization problem can be reduced to a new unconstrained one, which only relates to sensing time. Then the existence and uniqueness of optimal sensing time to achieve maximum energy-efficiency capacity are discussed and a low-complexity algorithm is proposed to obtain the optimal solution. Finally, numerical simulation is performed to verify the theoretical analysis results. The simulation results indicate that hybrid spectrum sharing is remarkably beneficial to energy-efficient transmission in cognitive radio networks （CRN）. And the proposed algorithm can quickly converge to the optimal solution.