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Precoding methods at the Base Station (BS) can be used to deal with the inter-cell interference and improve the signal quality of the user especially at the cell edge. In this paper, a novel Zero-Forcing (ZF) precoding method is proposed and investigated for multi-cell Multi-Input Multi-Output (MIMO) systems. We propose a relaxed ZF precoding method by relaxing the ZF criterion to some degree so that the inter-cell interference may not be zero. Complexity analysis shows that compared with the conventional ZF method, the additional computation complexity for the proposed method is trivial. Simulation results show that the proposed relaxed ZF method has better performance than the conventional ZF method in terms of the sum-rate, especially at low Signal to Noise Ratio (SNR).

Departing from the narrowband channel model, more and more researchers have recently considered the application of multiple-input multiple-output (MIMO) systems over frequency-selective fading channels in combination with the orthogonal frequency-division multiplexing (OFDM) technique. In this paper, we focus on the capacity of MIMO-OFDM systems and how to increase the capacity. It has been proved that the capacity of a MIMO system with space-dimensional water-filling power allocation is greater than that of the system with uniform power allocation. In MIMO-OFDM systems, there is an additional degree of freedom to allocate power with respect to MIMO systems: the OFDM sub-channels in frequency-domain. With the singular value decomposition (SVD) applied to the channel frequency response matrix, the two-dimensional water-filling power allocation algorithm for MIMO-OFDM systems is proposed based on the Lagrange method, and the corresponding capacity analysis formula is derived. Simulation results show that the capacity of a MIMO-OFDM system with the proposed two-dimensional water-filling power allocation is greater than that of the system with uniform power allocation and also greater than that of the system with the one-dimensional water-filling power allocation.

TH (Tomlinson-Harashima) precoding is an important nonlinear precoding method. In this paper, the bit error rate (BER) performance for the TH precoding system is investigated over time varying and dispersive Ricean fading channels. Assuming that there exists a certain delay introduced by the feedback channel, we first model the feedback error of channel station information (CSI) due to the feedback delay. Then the expression of the received signal over the time varying channel is derived. Finally, we analyze the power of interference signal resulting from the delay. Computer simulation shows that BER of the zero-forcing TH precoding system is inverse proportional to Ricean factor, and evident BER threshold occurs when the feedback delay is large.

In this paper, we consider the problem of blind channel estimation for single-input, single-output (SISO) system. Our main aim is to provide a new consideration in the subspace-based blind channel estimation. Instead of utilizing the noise subspace, as usually the case, we propose a new algorithm that makes use of the signal subspace signature. The new algorithm is shown to give a comparable performance with that of the noise subspace-based methods. A similar idea can be applied straightforwardly to single-input multiple-output (SIMO) and multiple-input multiple-output (MIMO) systems.

This paper develops a joint maximum a posteriori (MAP) spatial filtering receiver by employing a joint parameter estimation approach for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) modulation systems, which can achieve promising bit-error-rate (BER) performance in the presence of co-channel interference (CCI). For a MAP receiver to suppress the CCI, conventionally, this can be done in two ways: 1) spatio-temporal filtering (STF) the received signals prior to the fast Fourier transform (FFT), which we refer to it as preFFT-STF; 2) spatial filtering (SF) the received signals posterior to FFT, which is referred to as postFFT-SF. Simulation results show that the proposed scheme outperforms significantly both the preFFT-STF and postFFT-SF systems.

We develop an efficient hard-detector for multiple-input multiple-output (MIMO) channels, which adaptively combines maximum-likelihood detection (MLD) and minimum-mean-square-error (MMSE) with a successive interference canceler (SIC) together. Unlike the conventional joint combination scheme which may suffer from considerable degradation in bit-error-rate (BER) performance over correlated channels and where only one data stream is detected by MLD, our proposed scheme adaptively controls the number of data streams to be detected by MLD based on the analytical characterization of reliability for the detection. Simulation results illustrate that near-optimal BER performance can be obtained at much lower computational complexity by the proposed method as compared to existing techniques, regardless of the spatial correlation of the MIMO channels.