AMC 2015 Abstracts

Full Papers
Paper Nr: 1

Resource Allocation in SVD-assisted Broadband MIMO Systems Using Polynomial Matrix Factorization


André Sandmann, Andreas Ahrens and Steffen Lochmann

Abstract: Removing channel interference in broadband multiple-input multiple-output (MIMO) systems is a task which can be solved by applying a spatio-temporal vector coding (STVC) channel description and using singular value decomposition (SVD) in combination with signal pre- and post-processing. In this contribution a polynomial matrix factorization channel description in combination with a specific SVD algorithm for polynomial matrices is analyzed and compared to the commonly used STVC SVD. This comparison points out the analogies and differences of both equalization methods. Furthermore, the bit error rate (BER) performance is evaluated for two different channel types and is optimized by applying bit-allocation schemes involving a power loading strategy. Our results, obtained by computer simulation, show that polynomial matrix factorization such as polynomial matrix SVD could be an alternative signal processing approach compared to conventional SVD-based MIMO approaches in frequency-selective MIMO channels.

Paper Nr: 2

Antennas’ Correlation Influence on the GMD-assisted MIMO Channels Performance


César Benavente-Peces, Andreas Ahrens, José Manuel Pardo-Martín and Francisco Javier Ortega-González

Abstract: The use of multiple antennas in MIMO (multiple-input multiple-output) systems at both the transmit and receive sides produces the effect known as antennas correlation which impact the overall channel performance, throughput and bit-error rate (BER). The geometric mean decomposition (GMD) is a signal processing technique which can be used to process transmit and receive signals in MIMO channels. The GMD pre- and post-procesing in conjunction with dirty-paper precoding shows some advantages over the popular singular value decomposition (SVD) technique which provides GMD-assisted MIMO systems a superior performance particularly when the channel is affected by antennas correlation. This paper analyses the impact of antennas correlation on the performance of GMD-assisted wireless MIMO channels highlighting the advantages over SVD-assisted ones.

Paper Nr: 4

Efficient Soft-output Detectors - Multi-core and GPU implementations in MIMOPack Library


Carla Ramiro Sánchez, Antonio M. Vidal Maciá and Alberto Gonzalez Salvador

Abstract: Error control coding ensures the desired quality of service for a given data rate and is necessary to improve relaibility of Multiple-Input Multiple-Output (MIMO) communication systems. Therefore, a good combination of detection MIMO schemes and coding schemes has drawn attention in recent years. The most promising coding schemes are Bit-Interleaved Coded Modulation (BICM). At the transmitter the information bits are encoded using an error-correction code. The soft demodulator provides the reliability information in form of real valued log-likehood ratios (LLR). These values are used by the channel decoder to make final decisions on the transmitted coded bits. Nevertheless, these sophisticated techniques produce a significant increase in the computational cost and require large computational power. This paper presents a set of Soft-Output detectors implemented in CUDA and OpenMP, which allows to considerably decrease the computational time required for the data detection stage in MIMO systems. These detectors will be included in the future MIMOPack library, a High Performance Computing (HPC) library for MIMO Communication Systems. Experimental results confirm that these implementations allow to accelerate the data detection stage for different constellation sizes and number of antennas.