In this letter, we investigate the application of Tomlinson-Harashima precoding (THP) in the downlink of multiuser multiple-input multiple-output (MIMO) systems, where multiple antennas are located at all the transceivers. Based on the criterion of maximum system sum-capacity, a per-layer optimization scheme is proposed, in which the subchannel ordering and transceiver filters design are generated. In the proposed scheme, the successive character of THP can be fully exploited, so that both the minimum cost of interference suppression and the maximum power and diversity gains can be implemented, and hence, the system sum-capacity can be improved effectively.

This paper presents a novel threshold-based selection scheme to combine adaptive transmit antenna selection with an adaptive quadrature amplitude modulation (AQAM) for a spatial multiplexing (SM) multiple-input multiple-output (MIMO) system with linear receivers in practical uncorrelated and correlated channel conditions. The proposed scheme aims to maximize the average spectral efficiency (ASE) for a given bit error rate (BER) constraint and also to lower the hardware complexity. Our simulations are run on a general MIMO channel model, under the assumption that the channel state information (CSI) is known at the receiver and the adaptive control signaling can be perfectly fed back to the transmitter. We deploy the low rank-revealing QR (LRRQR) algorithm in transmit antenna subset selection. LRRQR is computationally less expensive than a singular value decomposition (SVD) based algorithm while the two algorithms achieve similar error rate performances. We show that both the conventional AQAM scheme (i.e., without adaptive transmit antenna selection) and the SM scheme perform poorly in a highly correlated channel environment. We demonstrate that our proposed scheme provides a well-behaved trade-off between the ASE and BER under various channel environments. The ASE (i.e., throughput) can be maximized with a proper choice of the channel quality threshold and AQAM mode switching threshold levels for a target BER.

A multiple-input multiple-output software defined radio (MIMO-SDR) platform was developed for implementation of MIMO transmission and propagation measurement systems. This platform consists of multiple functional boards for baseband (BB) digital signal processing and frequency conversion of 5 GHz-band radio frequency (RF) signals. The BB boards have capability of arbitrary system implementation by rewriting software on reconfigurable devices such as field programmable gate arrays (FPGAs) and digital signal processors (DSPs). The MIMO-SDR platform employs hybrid implementation architecture by taking advantages of FPGA, DSP, and CPU, where functional blocks with the needs for real-time processing are implemented on the FPGAs/DSPs, and other blocks are processed off-line on the CPU. In order to realize the hybrid implementation, driver software was developed as an application program interface (API) of the MIMO-SDR platform. In this paper, hardware architecture of the developed MIMO-SDR platform and its software implementation architecture are explained. As an application example, implementation of a real-time MIMO channel measurement system and initial measurement results are presented.

Multiple-input multiple-output (MIMO) systems using eigenbeam space division multiplexing (E-SDM) perform well and have increased capacities compared with those using conventional space division multiplexing (SDM). However, channel state information (CSI) is required at a transmitter, and the performance of E-SDM systems depends much on the accuracy of the CSI at a transmitter and a receiver. In time-varying fading environments, the channel change between the transmit weight determination time and the actual data transmission time causes the system performance to degrade. To compensate for the channel error, a linear extrapolation method has been proposed for a time division duplexing system. Unfortunately, the system performance still deteriorates as the maximum Doppler frequency increases. Here, two new techniques of channel extrapolation are proposed. One is second order extrapolation, and the other is exponential extrapolation. Also, we propose maximum Doppler frequency estimation methods for exponential extrapolation. Simulation results for 4tx 4rx MIMO systems showed that using the proposed techniques, E-SDM system performs better in a higher Doppler frequency region.

We developed two types of practical maximum-likelihood detectors (MLD) for multiple-input multiple-output (MIMO) systems, using a field programmable gate array (FPGA) device. For implementations, we introduced two simplified metrics called a Manhattan metric and a correlation metric. Using the Manhattan metric, the detector needs no multiplication operations, at the cost of a slight performance degradation within 1 dB. Using the correlation metric, the MIMO-MLD can significantly reduce the complexity in both multiplications and additions without any performance degradation. This paper demonstrates the bit-error-rate performance of these MLD prototypes at a 1 Gbps-order real-time processing speed, through the use of an all-digital baseband 44 MIMO testbed integrated on the same FPGA chip.

The discovery of the Turbo codes has driven research on the creation of new signal detection concepts that are, in general, referred to as the Turbo approach. Recently, this approach has made a drastic change in creating signal detection techniques and algorithms such as equalization of inter-symbol interference (ISI) experienced by broadband single carrier signaling over mobile radio channels. A goal of this paper is to provide readers with broad views and knowledge of the Turbo concept-based Multiple-Input Multiple-Output (MIMO) signal transmission techniques. How the techniques have been developed in various applications and how they perform in real-field environments are introduced.

We consider space division multiplexing in a MIMO-OFDM system for high data rate transmission. Channel estimation is very important for suppressing interference and demultiplexing signals. In a wireless LAN system such as IEEE 802.11a, only a few training symbols are inserted in each subcarrier. First, we propose a channel estimation method for a MIMO-OFDM system with two training symbols per subcarrier. The basic idea is to estimate the time-domain channel responses between the transmit and receive antennas. The array response vectors for each subcarrier are calculated by applying a fast Fourier transform to them. We then can obtain the adaptive weights to cancel the interference. We show that employing training symbols having a lower condition number of the matrix used for the channel estimation improves the estimation accuracy. Furthermore, we show the bit error rate for several signal detection schemes using the above estimated channel. It is shown that an ordered successive detection based on an MMSE criterion has excellent performance, that is, it can achieve higher-speed transmissions with a lower transmit power.