This paper addresses the problem of channel estimation for multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM)-based wireless networks with frequency-reuse. Firstly, the optimal time-domain training sequences are derived for the multiple cells with the same frequency group and a set of suitable sequences are also presented for practical implementation. Secondly, a low complexity iterative algorithm is combined with the time domain channel estimation to suppress the co-channel interferences (CCIs). The channel estimation method is applied to synchronous and asynchronous cellular and the MSE performance of the estimator is also analyzed. Simulation results demonstrate that the presented channel estimation approach can substantially suppress CCIs and outperform the conventional LS MIMO-OFDM channel estimation over multipath fading channels in multicell environments.

Free probability theory, which has become a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how the asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radio. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance than the energy detection techniques and the Maximum-minimum eigenvalue (MME) scheme even for the case of a small sample of observations.

A simple yet effective time domain correlation channel estimation method is proposed for multiple-input multiple-output (MIMO) systems over dispersive channels. It is known that the inherent co-channel interference (CCI) and inter-symbol interference (ISI) coexist when the signals propagate through MIMO frequency selective channels, which renders the MIMO channel estimation intractable. By elaborately devising the quasi-orthogonal training sequences between multiple antennas which have constant autocorrelation property with different cyclic shifts in the time domain, the interferences induced by ISI and CCI can be simultaneously maintained at a constant and identical value under quasi-static channels. As a consequence, it is advisable to implement the joint ISI and CCI cancelation by solving the constructed linear equation on the basis of the correlation output with optional correlation window. Finally, a general and simplified closed-form expression of the estimated channel impulse response can be acquired without matrix inversion. Additionally, the layered space-time (LST) minimum mean square error (MMSE) (LST-MMSE) frequency domain equalization is briefly described. We also provide some meaningful discussions on the beginning index of the variable correlation window and on the cyclic shift number of m-sequence of other antennas relative to the first antenna. Simulation results demonstrate that the proposed channel estimation approach apparently outperforms the existing schemes with a remarkable reduction in computational complexity.

Adaptive hybrid genetic algorithm concatenated with improved parallel interference cancellation, i.e. adaptive hybrid genetic algorithm parallel interference cancellation (AHGAPIC) was proposed. A study is conducted on the application of AHGAPIC to soft decoding high rate multi-user detection with diversity reception for dual-rate wideband DS-CDMA spread spectrum communications, aiming to mitigate the effect of multiple access interference. The relevant research has revealed that the local search capability of hybrid genetic algorithm (HGA) is still not good enough. Therefore, first, two evolutionary operations, i.e. inversion and insertion are merged into HGA to constitute a novel algorithm. With its moderate local search capability, this new algorithm can search for the global optimum region according to the information entropy, and then it is made adaptively vary its probabilities of crossover and mutation depending on the fitness values of the solutions to form the adaptive hybrid genetic algorithm (AHGA). Second, AHGA is utilized to effectively identify the better and better binary string to maximize the log-likelihood function of dual-rate multi-user detection. As AHGA converges to the optimum region, the control factor of the improved parallel interference cancellation (IPIC) detector is set to be the ratio of the average fitness value to the maximum fitness value of the population of AHGA. Finally, equipped with both the control factor and the binary string with the maximum fitness value as the initial data, the IPIC detector can rapidly find out the approximately optimum soft decoding vector. Then, it can obtain the approximately global optimum estimate point on the basis of the soft decoding rule, corresponding to the transmitted data bits. A lower bound of computational complexity has been achieved through simulations and qualitative analyses. The property of the proposed algorithm to converge rapidly leads to lower computational complexity. Emulation results have shown that the AHGAPIC soft decoding high rate multi-user detector is superior to other suboptimum detectors considered in this paper in terms of two points. They are the mitigation of multiple access interference and the resistance to near-far effects. Its performance is close to the sequential group optimum multi-user detector but with a shorter time delay.

The issue of importance of multiuser detection for CDMA-based mobile ad hoc networks is addressed in this paper. For conventional scheme, each terminal in the network uses matched filter to receive packets, so the performance (e.g., throughput) of the network suffers from multi-access interference (MAI). Different from above scheme, in this paper, each terminal of the ad hoc network is equipped with an adaptive blind linear multiuser detector, so the ability of MAI-resistance is gained. Employing slotted-ALOHA protocol in MAC layer and using fully-connected network model, the throughput of ad hoc network is studied. Theoretic analysis and simulation results show that multiuser detection can remarkably improve throughput performance of ad hoc networks.

Based on Free Probability Theory (FPT), which has become an important branch of Random Matrix Theory (RMT), a new scheme of frequency band sensing for Cognitive Radio (CR) in Direct-Sequence Code-Division Multiple-Access (DS-CDMA) multiuser network is proposed. Unlike previous studies in the field, the new scheme does not require the knowledge of the spreading sequences of users and is related to the behavior of the asymptotic free behavior of random matrices. Simulation results show that the asymptotic claims hold true even for a small number of observations (which makes it convenient for time-varying topologies) outperforming classical energy detection scheme and another scheme based on random matrix theory.