Francesc Rey

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.

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.

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.

Asymptotic and Finite User PER Analysis of Successive Interference Cancellation for DS-CDMA

An expression is derived for the average Packet Error Rate (PER) of a Successive Interference Canceller (SIC) for DS-CDMA when the number of users asymptotically tends to infinity. The asymptotic probability density function of the interference power is governed by a Fokker-Planck differential equation with drift and (asymptotically vanishing) diffusion depending on the PER function of the adopted forward error correcting code (FEC). In addition to the asymptotic solution for the PER, a particle-based algorithm is also developed for computing efficiently the PER in the finite user case.

Coded BER minimization for MIMO multicarrier systems with imperfect channel estimates

Linear transmitter designs that minimize the MSE or the uncoded BER do not guarantee good bit error performance when any channel correction code is introduced. As an alternative, the cutoff rate, that has been considered for a long time as the practical bound on the performance that could be achieved by finite length channel codes, can provide a good performance not for an specific channel code but for the average over the ensemble of codes with block length N. This work presents a robust power allocation strategy that maximizes the cut-off rate using partial channel state information (CSI) at the transmitter. A Bayesian formulation is used to design an optimal transmitter when CSI is noisy. A closed-form solution for the transmitter design is obtained. In addition, the design adapts to the CSI quality, providing an algorithm that tends to the open-loop design when no CSI is available at the transmitter (i.e., the same power is allocated across all antennas and subcarriers).

Transmitter channel tracking for optimal power allocation

The design of accurate equalization schemes, optimizing the transmission strategy, can be achieved if channel status information is available not only at the receiver but also at the transmitter side. Accordingly, we propose a feasible scheme to track the channel response by the transmitter based on channel prediction, becoming a suitable solution in time-varying channels. Moreover, to follow faithfully the channel variability, the receiver can estimate the channel prediction error and next update the transmitter predictor through a return link. This paper provides an accurate study of the predictor design, and analyzes the way to minimize the amount of information exchanged through the feedback channel concerning the differential entropy of channel evolution. Furthermore, the prediction error is quantified focusing on the rate-distortion function, and it is shown that a low throughput is enough for tracking the channel coefficients even in the presence of fast time-varying channels.

Redundancy in block coded modulations for channel equalization based on spatial and temporal diversity

Linear block codes in the complex field can be applied in spatial and/or temporal diversity receivers in order to develop high performance schemes for (almost-) blind equalization in mobile communications. The proposed technique uses the structure of the encoded transmitted information (with redundancy) to achieve equalization schemes based on a deterministic criterion. Simulations show that the proposed technique is more efficient than other schemes that follow similar equalizer structures. The result is an algorithm that provides the design of channel equalizers in low EbNo scenarios.