In this letter, we present a multiple-input multiple-output (MIMO) optimal combining (OC) scheme based on alternate iteration. With the channel state information (CSI) of co-channel interferers (CCIs), this algorithm can be used in flat fading and frequency selective channels to suppress CCIs. Compared with the optimal transceiver of MIMO maximal ratio combining (MRC) systems, results of simulation show that this scheme improves the uplink transmission performance significantly.

In this paper, the performance of multiuser MIMO E-SDM systems in downlink transmission is evaluated in both uncorrelated and correlated time-varying fading environments. In the ideal case, using the block diagonalization scheme, inter-user interference can be completely eliminated at each user; and using the E-SDM technique for each user, optimal resource allocation can be achieved, and spatially orthogonal substreams can be obtained. Therefore, a combination of the block diagonalization scheme and the E-SDM technique applied to multiuser MIMO systems gives very good results. In realistic environments, however, due to the dynamic nature of the channel and processing delay at both the transmitter and the receiver, the channel change during the delay may cause inter-user interference even if the BD scheme is used. In addition, the change may also result in large inter-substream interference and prevent optimal resource allocation from being achieved. As a result, system performance may be degraded seriously. To overcome the problem, we propose a method of channel extrapolation to compensate for the channel change. Applying our proposed method, simulation results show that much better system performance can be obtained than the conventional case. Moreover, it also shows that the system performance in the correlated fading environments is much dependent on the antenna configuration and the angle spread from the base station to scatterers.

In multiple antenna systems that use spatial multiplexing to raise transmission rates, it is preferable to use maximum likelihood (ML) detection to exploit the full receive diversity and minimize the error probability. In this paper, we present two tree based approximate ML detectors that use new two ordering criteria in conjunction with efficient search strategies. Unlike conventional tree detectors, the new detectors closely approximate the error performance of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, they ensure a fixed detection delay and high level of parallelization in the tree search.

A detector for space-time block coding is proposed to combat time-selective fading. To suppress both noise and interference, a minimum mean square error (MMSE) based detector is introduced for space-time block coding. It is shown by simulations that the proposed detector outperforms the conventional detectors when the channel is time-selective fading.

In this letter, a codebook based multiuser MIMO precoding scheme is proposed for a space-division multiple access (SDMA) system with limited feedback. Focusing on the case of SDMA systems with two transmit antennas, a precoder codebook design is proposed based on the idea that a precoder inducing larger fluctuations in the signal to interference and noise ratio (SINR) at each link can lead to a larger gain in terms of multiuser diversity. It is shown that the proposed multiuser MIMO precoding outperforms existing multiuser MIMO techniques in terms of the average system throughput.

In multiple-input multiple-output (MIMO) wireless systems, the receiver must extract each transmitted signal from received signals. Iterative signal detection with belief propagation (BP) can improve the error rate performance, by increasing the number of detection and decoding iterations in MIMO systems. This number of iterations is, however, limited in actual systems because each additional iteration increases latency, receiver size, and so on. This paper proposes a convergence acceleration technique that can achieve better error rate performance with fewer iterations than the conventional iterative signal detection. Since the Log-Likelihood Ratio (LLR) of one bit propagates to all other bits with BP, improving some LLRs improves overall decoder performance. In our proposal, all the coded bits are divided into groups and only one group is detected in each iterative signal detection whereas in the conventional approach, each iterative signal detection run processes all coded bits, simultaneously. Our proposal increases the frequency of initial LLR update by increasing the number of iterative signal detections and decreasing the number of coded bits that the receiver detects in one iterative signal detection. Computer simulations show that our proposal achieves better error rate performance with fewer detection and decoding iterations than the conventional approach.

Multi-user MIMO (Multiple Input Multiple Output) systems, in which multiple Mobile Stations (MSs) equipped with multiple antennas simultaneously communicate with a Base Station (BS) equipped with multiple antennas, at the same frequency, are attracting attention because of their potential for improved transmission performance in wireless communications. In the uplink of Space Division Multiplexing based multi-user MIMO (multi-user MIMO/SDM) systems that do not require full Channel State Information (CSI) at the transmitters, selecting active MS antennas, which corresponds to scheduling transmit antennas, is an effective technique. The Full search Selection Algorithm based on exhaustive search (FSA) has been studied as an optimal active MS antenna selection algorithm for multi-user MIMO systems. Unfortunately, FSA suffers from extreme computational complexity given large numbers of MSs. To solve this problem, this paper introduces the Gram-Schmidt orthogonalization based Selection Algorithm (GSSA) to uplink multi-user MIMO/SDM systems. GSSA is a suboptimal active MS antenna selection algorithm that offers lower computational complexity than the optimal algorithm. This paper evaluates the transmission performance improvement of GSSA in uplink multi-user MIMO/SDM systems under realistic propagation conditions such as spatially correlated BS antennas and clarifies the effectiveness of GSSA.

While significant work has been dedicated to analyzing the performance of antennas for multiple-input multiple-output (MIMO) and diversity systems, little has appeared on synthesizing optimal antennas for these systems. This paper explores optimal antenna characteristics given understanding about the average structure of the propagation environment, making the results applicable for time-varying channels created by mobile nodes or scatterer motion. Specifically, it examines optimal antenna designs for the cases where 1) the antennas reside in a fixed aperture or 2) the number of antenna elements is fixed (under fast-fading conditions with spatially correlated signals).

In time-varying fading environments, the performance of multiple-input multiple-output (MIMO) systems applying an eigenbeam-space division multiplexing (E-SDM) technique may be degraded due to a channel change during the time interval between the transmit weight matrix determination and the actual data transmission. To compensate for the channel change, we have proposed some channel prediction methods. Simulation results based on computer-generated channel data showed that better performance can be obtained when using the prediction methods in Rayleigh fading environments assuming the Jakes model with rich scatterers. However, actual MIMO systems may be used in line-of-sight (LOS) environments, and even in a non-LOS case, scatterers may not be uniformly distributed around a receiver and/or a transmitter. In addition, mutual coupling between antennas at both the transmitter and the receiver cannot be ignored as it affects the system performance in actual implementation. We conducted MIMO channel measurement campaigns at a 5.2 GHz frequency band to evaluate the channel prediction techniques. In this paper, we present the experiment and simulation results using the measured channel data. The results show that robust bit-error rate performance is obtained when using the channel prediction methods and that the methods can be used in both Rayleigh and Rician fading environments, and do not need to know the maximum Doppler frequency.

In this paper, we evaluate BER (bit error rate) performance and diversity gain when employing a transmission technique utilizing LC (Linear Combination) diversity using 2 time slots with QPSK channels in 2 2 MIMO (Multiple-Input Multiple-Output) spatial multiplexing systems by comparing it with the upper and lower bound on BER. This evaluation shows that this transmission technique realizes high diversity gain and high transmission rate in LOS (line-of-sight) and NLOS (non line-of-sight) environments.

We propose a new broadcast strategy for a multiple-input multiple-output (MIMO) system with N transmit antennas at the transmitter and M≤N single antenna receivers. The proposed method, based on dirty-paper coding (DPC), spatially separates the M users but does not suffer from the power loss of classical spatial division multiple access (SDMA). For the special case of M=N=2 and when the two single antenna receivers are assumed to be co-located, the proposed scheme produces a 2 transmit, 2 receiver antenna MIMO transmission system that doubles the symbol rate of MIMO space-time block code (STBC) systems from one to two symbol per transmission time. It is proved theoretically and experimentally that the proposed scheme provides the same performance level as that of MIMO STBC systems (i.e., the Alamouti scheme) for the first symbol, and the same performance as the Bell labs layered space-time (BLAST) system for the second symbol. When compared to the BLAST system, the proposed scheme has the same symbol rate, but achieves significantly better performance, since it provides 2 level diversity per symbol on the first symbol while the BLAST system does not provide any diversity.

In a frequency-selective multiple-input multiple-output (MIMO) channel, the optimum transmission is achieved by beamforming with eigenvectors obtained at each discrete frequency point, i.e., an extension of eigenbeam-space division multiplexing (E-SDM). However, the calculation load of eigenvalue decomposition at the transmitter increases in proportion to the number of frequency points. In addition, frequency-independent eigenvectors increase the delay spread of the effective channel observed at the receiver. In this paper, we propose a pseudo eigenvector scheme for the purpose of mitigating the calculation load and maintaining frequency continuity (or decreasing the delay spread). First, we demonstrate that pseudo eigenvectors reduce the delay spread of the effective channels with low computational complexity. Next, the practical performance of the pseudo E-SDM (PE-SDM) transmission is evaluated. The simulation results show that PE-SDM provides almost the same or better performance compared with E-SDM when the receiver employs a time-windowing-based channel estimation available in the low delay spread cases.

In this paper, a computationally efficient stack-based iterative detection algorithm is proposed for V-BLAST systems. To minimize the receiver's efforts as much as possible, the proposed scheme employs iterative tree search for complexity reduction and storage saving. After an M-ary tree structure by QR decomposition of channel matrix is constructed, the full tree depth is divided into the first depth and the remaining ones. At tree depth of one, the proposed algorithm finds M candidate symbols. Based on these symbols, it iteratively searches the remaining symbols at second-to-last depth, until finding an optimal symbol sequence. Simulation results demonstrate that the proposed algorithm yields the performance close to that of sphere detection (SD) with significant saving in complexity and storage.

We propose a geometric mean decomposition (GMD) based vector precoding (VP) for multiple input multiple output (MIMO) systems. Minimum mean square error (MMSE) criterion is used for the joint VP design. The application of GMD method eliminates the imbalance among subchannel gains and obtains a better perturbation vector than the conventional method. We then exploit the extended channel matrix for further performance improvement. Simulation results show the proposed schemes significantly outperform the existing VP schemes.

In this letter, the system capacity of multiuser diversity combined with spatial multiplexing schemes is analyzed. An analytic expression is derived for the ergodic system capacity with multiuser scheduling and dual multi-input multi-output (MIMO) systems by using a tight lower bound of the link capacity. The proposed analytic approach is verified through comparisons between analytic and simulated results, and is shown to make fairly precise predictions of the ergodic system capacity and the scheduling gains even when the numbers of antennas and users are small.

In this letter, we elucidate the ergodic capacity of multiple-input multiple-output (MIMO) systems with M-ary phase-shift keying (MPSK) modulation and time-multiplexed pilots in frequency-flat Rayleigh fading environment. With linear minimum mean square error (LMMSE) channel estimation, the optimal pilots design is presented. For mathematical tractability, we derive an easy-computing closed-form lower bound of the channel capacity. Based on the lower bound, the optimal power allocation between the data and pilots is also presented in closed-form, and the optimal training length is investigated by numerical optimization. It is shown that the transmit scheme with equal training and data power and optimized training length provides suboptimal performance, and the transmit scheme with optimized training length and training power is optimal. With the latter scheme, in most situations, the optimal training length equals the number of the transmit antennas and the corresponding optimal power allocation can be easily computed with the proposed formula.

This paper proposes an adaptive transmission scheme for MIMO systems to provide different bit error rates and transmission rates for multimedia traffic. The adaptive transmission scheme allocates antennas, rate and power jointly according to the feedback information to satisfy the diverse QoS requirements of the multimedia traffic. Furthermore, an efficient search algorithm with low complexity is proposed for practical implementation. Simulation results show that the proposed scheme improves the spectral efficiency while guaranteeing the QoS requirements of multimedia traffic. Moreover, the proposed search algorithm achieves close optimal performance with great complexity reduction.

Recent work has shown that the usage of multiple antennas at the transmitter and receiver in a flat fading environment results in a linear increase in channel capacity. But increasing the number of antennas induces the higher hardware costs and computational burden. To overcome those problems, it is effective to select antennas appropriately among all available ones. In this paper, a new antenna selection method is proposed. The transmit antennas are selected so as to maximize the channel capacity using the genetic algorithm (GA) which is the one of the general random search algorithm. The results show that the proposed GA achieves almost the same performance as the optimal selection method with less computational amount.

This paper proposes a new detection ordering scheme, which minimizes average error rate of the MIMO system with per antenna rate control. This paper shows an optimal scheme minimizing average error rate expressed by the Q function, and simplifies the optimal scheme by using the minimum equivalent SINR scaled by modulation indices, based on approximated error rate. In spite of reduced complexity, the simplified scheme demonstrates the almost same performance as the optimal scheme. Owing to the diversity of detection ordering, the proposed scheme has over 2 dB higher SNR gain at the BER of 10-3 than the existing ordering schemes in balanced array size systems.

The enormous capacity potential of multiple-input multiple-output (MIMO) is based on some unrealistic assumptions, such as the complete channel state information (CCSI) at the receiver and Gaussian distributed data. In this paper, in frequency-flat Rayleigh fading environment, we investigate the ergodic capacity of MIMO systems with M-ary phase-shift keying (MPSK) modulation and superimposed pilots for channel estimation. With linear minimum mean square error (LMMSE) channel estimation, the optimal pilots design is presented. For the mathematical tractability, we also derive an easy-computing closed-form lower bound of the channel capacity. Furthermore, the optimal power allocation between the data and pilots is investigated by numerical optimization. It is shown that more power should be devoted to the data in low SNR environments and to the pilots in high SNR environments.