Hans Weinrichter

Approximate ML detection for MIMO systems with very low complexity

Recently many space-time coding schemes for multiple antenna systems (MIMO) have been proposed in order to achieve high data rates when transmitting over wireless channels. However, most of such schemes rely on maximum likelihood (ML) detection, which can become quite complex when many antennas are involved and higher modulation schemes are utilized. On the other hand, the high diversity gains of MIMO channels are easily lost when low-complexity receivers like ZF or MMSE are applied. It is thus of utmost importance to look for low-complexity receivers which achieve almost ML performance. In this paper, a new scheme for approximate ML detection for typical flat Rayleigh fading channels is proposed, achieving ML performance in the area of bit error ratio between 10/sup -4/ and 0.1 as it is of interest in wireless communications. The proposed scheme allows the transmission of 64QAM schemes on 4/spl times/4 antenna schemes with a detection complexity of only 1% of a brute force ML receiver.

Extended Alamouti codes in correlated channels using partial feedback

In this paper we present a family of quasi-orthogonal space-time codes for correlated MIMO (multi-input/multi-output) channels using four and eight transmit antennas when only partial channel state information is sent back to the transmitter. Transmit diversity is improved up to nearly the optimum diversity value. This high diversity can be exploited with zero forcing receivers as well as with maximum-likelihood receivers.

Quasi-orthogonal space-time block codes on measured MIMO channels

In this paper we study the performance of quasi-orthogonal space-time block codes (QSTBCs) on measured MIMO channels using four transmit and four receive antennas. We use QSTBCs with and without partial channel state information at the transmitter At the receiver we compare a zeroforcing receiver and a maximum likelihood receiver We demonstrate that applying our simple feedback scheme, the QSTBCs are robust against different MIMO channel realizations and they perform very well even in case of spatial channel correlations.

Adaptive subspace modulation in spatially correlated MIMO systems

We propose an adaptive modulation scheme for wireless MIMO systems. The main goal of this scheme is to maximize the bit rate for a fixed target BER. The MIMO channel is split up into several independent channels (subspaces) by a singular value decomposition. On each of these independent channels, the modulation format is adapted to the subchannel SNR. The proposed algorithm allocates appropriate modulation schemes from 2PSK to 256QAM to each subchannel. The channel is assumed to be quasi static flat Rayleigh fading, perfectly known at both ends of the link. Mean data rates that can be obtained are presented as a function of the mean SNR, keeping BER below a target value of, e.g., 10/sup -3/ for spatially uncorrelated and partially correlated channels without using any error correcting code.

Performance of various data transmission methods on measured MIMO channels

We discuss the performance of several data transmission schemes over measured MIMO-channels using four transmit antennas. We analyze uncoded and prefiltered data transmission with schemes using simple extended Alamouti codes, with and without partial feedback. Our simulations are based on channel measurements and measurement based channel models. It is shown that the extended Alamouti scheme using partial feedback is extremely robust against channel correlation and thus outperforms other transmission schemes.

ECG signal coding using wavelet transform and binary arithmetic coder

A new system for ECG compression using the discrete wavelet transform (DWT) is presented. We propose a new method to code the quantized wavelet coefficients. This way of coding exploits both the sparseness and the self-similarity amongst the subbands. It helps to increase the performance compared to other methods also based on the wavelet transform. On average, a compression ratio of more than 10 can be attained with a PRD less than 4%.

A new binary source coder and its application in bi-level image compression

We present a new binary source coder. The new coder is a combination of many truncated-run-length coders governed by an adaptive probability estimation process. The estimation process can be implemented effectively as a finite-state machine. We apply the new coder to lossless bi-level image compression and compare the results with state-of-the-art methods. The results indicate that the new coder is comparable to current ones. The proposed coder is very simple for hardware and software implementation.

A union bound of the bit error ratio for data transmission over correlated wireless MIMO channels

In this contribution we derive a union bound of the bit error ratio (BER) in wireless multiple input multiple output (MIMO) data transmission systems using maximum likelihood (ML) receivers. A novel channel model is used to take into account channel correlation. Relying on the Euclidean distance between different transmit signals, we show that the error performance is governed by a few so-called error types (ET). Simulation results are shown for a 4x4 MIMO system with BPSK modulation and for a 2x2 MIMO system with 16QAM modulation for several channel correlations. Our union bound becomes tight for low BER for all MIMO systems under investigation.

Comparison of nonorthogonal space-time block codes using partial feedback in correlated channels

We analyze and compare transmission schemes that apply nonorthogonal space-time block codes in uncorrelated and correlated MIMO channels using four transmit antennas and a zero-forcing receiver. The ABBA code and a slightly different code, the so-called extended Alamouti code (EAC) are compared. For both codes, partial channel state information is sent back from the receiver to the transmitter quantized to one bit per code block. In this way, we improve the diversity of signal transmission and decorrelate the system using the ABBA code as well as the EAC.

DWT image compression using contextual bitplane coding of wavelet coefficients

Image coding using the discrete wavelet transform can attain very good results compared to traditional methods. In fact, most of the best known results for image coding have been related to the DWT. A simple scheme to code the DWT coefficients is the embedded zero-tree wavelet algorithm by Shapiro (1993). The embedded zero-tree wavelet can exploit both the similarity among subbands and the sparseness of the subbands. We propose a new simple image coder based on the DWT. The DWT coefficients are coded in bitplanes. Each bi-level pixel is coded in a context formed by its parental and surrounding pixels. In this way, both the similarity and the sparseness among subbands are exploited. We show the experimental results, both in terms of distortion measurement and visual comparison, and compare them to well-known methods.