Meritxell Lamarca

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimization criteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed, and their relationship with existing algorithms is indicated. As with other previously proposed solutions, the minimum bit error rate algorithm converges to the open-loop transmission scheme for very poor CSI estimates.

Analog Joint Source-Channel Coding Using Non-Linear Curves and MMSE Decoding

We investigate the performance of a discrete-time all-analog-processing joint source-channel coding system for the transmission of memoryless sources over average power constrained AWGN channels. First, N:1 bandwidth compression systems are analyzed and optimized. At the encoder, N samples of an i.i.d. source are directly mapped into one channel symbol using a non-linear curve. Different from previous work in the literature, we introduce an additional degree of freedom at the encoder, MMSE decoding instead of ML decoding is considered, and we focus on both high and low channel signal-to-noise ratio (CSNR) regions. By using MMSE decoding, the proposed system presents a performance very close to the theoretical limits, even at low CSNR, as long as the system parameters are properly optimized. Then, N:K bandwidth compression systems are constructed by parallel combination of an M:1 system and a 1:1 uncoded system, and the optimal power allocation between the two constituent systems is derived in order to maximize the overall output signal-to-distortion ratio (SDR). Finally, 1:2 bandwidth expansion systems using mapping functions similar to those used in 2:1 system are investigated. Different from digital systems, the proposed scheme does not require long block lengths to achieve good performance, and shows graceful degradation when the CSNR is lower than the one used for the design.

Linear precoding for mutual information maximization in MIMO systems

We study the design of linear precoders for maximization of the mutual information in MIMO systems with arbitrary constellations and with perfect channel state information at the transmitter. We derive the structure of the optimum precoder and we show that the mutual information is concave in a quadratic function of the precoder coefficients. An iterative algorithm is also proposed to find this optimum value.

Analog Joint Source Channel Coding Using Space-Filling Curves and MMSE Decoding

We investigate the performance of a discrete-time all-analog-processing joint source channel coding system for the transmission of i.i.d. Gaussian and Laplacian sources over AWGN channels. In the encoder, two samples of an i.i.d. source are mapped into a channel symbol using a space-filling curve. Different from previous work in the literature, MMSE decoding instead of ML decoding is considered, and we focus on both high and low channel SNR regions. The main contribution of this paper is to show that the proposed system presents a performance very close to the theoretical limits, even at low SNR, as long as the curve parameters are properly optimized.

Indicators for PER prediction in wireless systems: A comparative study

A variety of problems such as link adaptation and power allocation require the estimation of the instantaneous packet error rate (PER) prior to the signal transmission. In the strict sense, this problem can only be solved if the dependence of the PER with the scenario (e.g. instantaneous fading value, noise power, etc) is known. However, some proposals have been made to simplify the problem summarizing this dependence into a single parameter. This paper compares some of them and introduces a new metric that takes into account the channel code structure, as opposed to previous ones.

Transmit filter optimization based on partial CSI knowledge for wireless applications

This paper deals with closed-loop schemes in OFDM modulation systems. A Bayesian approach is presented to design minimum BER prefiltering matrices in the presence of channel uncertainties. This formulation leads to a robust algorithm that exhibits lower sensitivity to channel estimation errors than classical schemes. The proposed design encompasses the single antenna transmission, the beamforming schemes and the frequency flat fading channels as particular cases.

Optimal power allocation with partial channel knowledge for MIMO multicarrier systems

Closed-loop schemes optimizing power allocation can be applied if channel status information (CSI) is available at both transmitter and receiver. However, CSI is never ideal and algorithms performance degrades rapidly when CSI is poor. In this contribution a MMSE cost function that takes into account channel uncertainty is proposed for MIMO systems with OFDM modulation. The derived algorithm is robust to channel estimation errors. A closed form solution is obtained for joint transmitter and receiver design that optimally allocates the power over all subcarriers and antennas. Numerical results show the new criterion outperforms other solutions that assume ideal CSI knowledge.

Multichannel receivers for OFDM and TDMA in mobile communications

This paper addresses the use of multichannel receivers for blind equalization in TDMA under frequency selective channels and OFDM systems in frequency flat fading channels. A new criteria is proposed for blind equalization of finite length mobile channels.

Linear Precoder Design Through Cut-Off Rate Maximization in MIMO-OFDM Coded Systems With Imperfect CSIT

This paper proposes a linear transmitter design that aims at minimizing the packet error rate (PER) using partial channel state information at the transmitter (CSIT). The design is based on the maximization of the channel cut-off rate, which provides an upper bound on the codeword error probability over the ensemble of random codes. The advantage of this optimization criterion is that it allows to get a low PER while keeping the design independent of the specific channel code used in the system. The algorithm is derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, and adopts a Bayesian approach to design an algorithm robust to CSI errors. The proposed algorithm converges to the open-loop transmission scheme for the case of no channel knowledge and it converges to the closed-loop design with perfect CSI for the case of no uncertainty. Simulation results evidence the performance gain in terms of PER and throughput of the proposed algorithm when compared to more commonly used optimization criteria.

Adaptive interleaver based on rate-compatible punctured convolutional codes

This letter focuses on the design of an adaptive bit-interleaved coded modulation (BICM) scheme for frequency selective slow fading channels where the transmitter has certain knowledge of the channel response. In particular, we consider the design of the interleaver stage for a specific convolutional code operating with OFDM modulation. The adaptive interleaver uses the puncturing tables of the rate-compatible punctured convolutional codes (RCPC codes) to rearrange the bits as a function of the fading values and the specific constellation. The performance of different interleavers are compared, revealing that the adaptive RCPC-based interleaver produces larger Euclidean distances between the received codewords and reduces the packet error rate (PER), specially when the number of deep-faded subcarriers increases. Numerical results also evidence the importance of the interleaver choice when comparing the performance of different power allocation strategies.