dB Performance Loss Research Articles

Reducing Detection Complexity of MIMO-OFDM by Using New Nulling Vectors

We propose new nulling vectors for the subcarrier grouping based low-complexity detection scheme of V-BLAST (vertical Bell Laboratories layered space-time) coded MIMO-OFDM. In each subcarrier group, the center subcarrier uses the conventional ZF-DFE (zero-forcing decision-feedback- equalization) algorithm and the non-center subcarriers use the reduced-complexity ZF-DFE with the new nulling vectors. The subcarrier grouping based detection scheme, ZF-DFE-SG, can significantly reduce the detection complexity compared with ZF-DFE-EX which exhaustively applies the conventional ZF-DFE at each subcarrier independently. The performance loss is very small. We conduct the simulations for channel coded V-BLAST OFDM system under estimated channel frequency responses. It is shown the complexity can be reduced by 80.6% with only 1.0 dB performance loss for a 4x4 system.

Differential Detection of Space-Time Spreading with Two Transmit Antennas

A differential detection scheme for space-time spreading with two transmit antennas is proposed. The scheme does not require channel state information at either the transmitter or the receiver. With segmentation and preamble symbols padded at the transmitter, the receiver recovers the information using differential detection. Both phase-shift keying (PSK) and quadrature amplitude modulation (QAM) signals are considered. The proposed scheme achieves two-level transmit diversity gain with low complexity and saves the use of channel estimation, while having about 3 dB performance loss as compared to the coherent detection scheme. When multiple receive antennas exist, additional receive diversity gain can be achieved along with the transmit diversity gain. The scheme works fine under block-fading channel as well as slow Rayleigh fading channel, which is a popular scenario for high-rate data communications. The system performance for different segment sizes, channel fading speeds, modulation methods, and numbers of receive antennas is studied through simulations.

On the rate-distortion performance and computational efficiency of the Karhunen-Loeve transform for lossy data compression

We examine the rate-distortion performance and computational complexity of linear transforms for lossy data compression. The goal is to better understand the performance/complexity tradeoffs associated with using the Karhunen-Loeve transform (KLT) and its fast approximations. Since the optimal transform for transform coding is unknown in general, we investigate the performance penalties associated with using the KLT by examining cases where the KLT fails, developing a new transform that corrects the KLT's failures in those examples, and then empirically testing the performance difference between this new transform and the KLT. Experiments demonstrate that while the worst KLT can yield transform coding performance at least 3 dB worse than that of alternative block transforms, the performance penalty associated with using the KLT on real data sets seems to be significantly smaller, giving at most 0.5 dB difference in our experiments. The KLT and its fast variations studied here range in complexity requirements from O(n(2)) to O(n log n) in coding vectors of dimension n. We empirically investigate the rate-distortion performance tradeoffs associated with traversing this range of options. For example, an algorithm with complexity O(n(3/2)) and memory O(n) gives 0.4 dB performance loss relative to the full KLT in our image compression experiments.