In this work,we consider an amplify-and-forward two-way multi-relay system for wireless communication and investigate the effect of channel estimation error on the error rate performance.With the derivation of effective signal-to-noise ratio at the transceiver and its probability density function,we can get approximate expression for average bit error rate.Simulation results are performed to verify the analytical results.
WANG Si-ye XU Wen-jun HE Zhi-qiang NIU Kai WU Wei-ling
This paper studies the problem of effective resource allocation for multi-radio access technologies (Multi-RAT) nodes in heterogeneous cognitive wireless networks (HCWNs). End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.
The recent increasing interest in cognitive radio networks has motivated the study and development of new approaches capable of coping with the intrinsic challenges of this kind of network,such as dynamic spectrum availability,distributed and heterogeneous network architectures,and soaring complexity.The bio-inspired approaches,with appealing characteristics such as autonomy,adaptation and collective intelligence of collaborative individuals,have been extensively studied.This paper presents a comprehensive survey of bio-inspired approaches for cognitive radio networks,emphasizing their domains of application.Specifically,ant colony optimization and particle warm optimization are further investigated with examples and numerical simulation.
HE ZhiQiangNIU KaiQIU TaoSONG TaoXU WenJunGUO LiLIN JiaRu
The resource allocation scheme for the multiple description coding multicast(MDCM) in orthogonal frequency division multiplexing(OFDM-based) cognitive radio network(CRN) is studied in this paper,aiming at maximizing the total throughput of cognitive radio(CR) users,with constraints on sum transmit power,the maximal receiving rate of each CR user and the maximal total interference introduced to each primary user.With the analysis of the model,an algorithm,which consists of subcarrier assignment and power allocation using the sub-gradient updating method,is proposed.Meanwhile,to reduce the complexity,a suboptimal algorithm is also proposed,which divides the total transmit power into small slices and allocates them one by one.Moreover,the suboptimal algorithm is modified by adding an advanced water-filling process to improve the performance.The simulation results obtained in this paper show that the system throughput using the MDCM scheme is much higher than that using the conventional multicast(CM) scheme and the performance of the proposed suboptimal algorithms can approximate the MDCM scheme very well.
In this paper,a frequency domain decision feedback equalizer is proposed for single carrier transmission with time-reversal space-time block coding (TR-STBC).It is shown that the diagonal decision feedback equalizer matrix can be calculated from the frequency domain channel response.Under the perfect feedback assumption,the proposed equalizer can approach matched filter bound (MFB).Compared with the existing time domain decision feedback equalizer,the proposed equalizer exhibits better performance with the same equalization complexity.
In this paper,we consider the downlink channel of multi-user multi-input single-output(MU-MISO)system in cognitive radio network,where the cognitive base station(CBS)resort to beamforming scheme to relief co-channel interference.The design criterion is to minimize the transmit power at CBS,subject to the signal-to-interference-plus-noise-ratio(SINR)constraints of cognitive users(CUs)and the interference constraints at primary users(PUs).Standard conic optimization packages can handle the problem,however,the complexity is very high and optimization packages are not always available.Basing on the karush-kuhn-tucker(KKT)conditions of the converted optimization problem,we proposed an iteration algorithm.Simulation results reveal that the proposed algorithm can converge to the optimal beamforming vectors that lead to minimum transmit power with all constraints satisfied.
A novel scheme to joint phase noise (PHN) correcting and channel noise variance estimating for orthogonal frequency division multiplexing (OFDM) signal was proposed. The new scheme was based on the variational Bayes (VB) method and discrete cosine transform (DCT) approximation. Compared with the least squares (LS) based scheme, the proposed scheme could overcome the over-fitting phenomenon and thus lead to an improved performance. Computer simulations showed that the proposed VB based scheme outperforms the existing LS based
