Florence Alberge

Adaptive solution for blind identification/equalization using deterministic maximum likelihood

A deterministic maximum likelihood (DML) approach is presented for the blind channel estimation problem. It is first proposed in a block version, which consists of iterating two steps, each one solving a least-squares problem either in the channel or in the symbols. In the noiseless case and under certain conditions, this algorithm gives the exact channel and the exact symbol vector with a finite number of samples. It is shown that even if the DML method has a single global minimum, the proposed iterative procedure can converge to spurious local minima. This problem can be detected (under some channel diversity conditions) by using a numerical test that is proposed in the paper. Based on these considerations, we extend the maximum likelihood block algorithm (MLBA) to recursive implementations [maximum likelihood recursive algorithm (MLRA)]. The MLRA is able to track variations of the system by the introduction of an exponential forgetting factor in the DML criterion. The link between the adaptive algorithm and a soft decision feedback equalizer (SDFE) is emphasized. Low-complexity versions of the recursive and adaptive algorithm are presented.

A posteriori control of complex Reed Solomon decoding with application to impulse noise cancellation in HIPERLAN/2

In OFDM systems, pilot tones are emitted for synchronization or channel estimation purposes. These pilot tones are generally scattered among the information ones. Our approach is to use these pilot tones as syndromes, in order to correct impulse noise. We previously proposed (see Abdelkefi, F. et al., ISSPA, 2001) a decoding algorithm in three steps: (1) estimate the amount of impulse noise; (2) seek the location; (3) correct the errors. A protection subsystem was introduced after the decoding operation in order to detect malfunction. Indeed, we added a control step which is able to estimate carefully whether the decoding procedure has worked correctly. We now explain this a posteriori control which is based on the hypothesis test. This approach is new in impulse noise cancellation in multicarrier transmission. The efficiency of this technique is also corroborated with simulations in the practical context of HIPERLAN/2.

A Necessary Condition on the Location of Pilot Tones for Maximizing the Correction Capacity in OFDM Systems

This paper presents a new view of the Bose-Chaudhuri-Hocquengem (BCH) code through the addition of some flexibility to the syndromes distribution in the transmitted sequence. In order to get this flexibility, we derive a necessary condition (NC) on the syndromes distribution for decoding BCH codes, which includes the already known Hartmann-Tzeng proposition. This NC is essentially deduced from the decoding process of BCH code, and is related to the locator polynomial and the requested constraints to guarantee a maximal error-correction capacity. The obtained results have the advantage to be applicable for any considered field (finite or not). Furthermore, we prove that when the correction capacity is equal to 2 or 3, the obtained NC becomes also sufficient. This result is very useful in some practical transmission systems such as orthogonal frequency-division multiplexing systems. Once the pilot tones considered in such systems verify the necessary and sufficient condition, it becomes possible to both reduce the peak-to-average-power rate and correct the impulse noise, present in such multicarrier systems. The usefulness of the presented analysis and the exploitation of the derived condition on the pilot tones distribution is illustrated by simulation results in the case of the Hiperlan2 system

Blind identification/equalization using deterministic maximum likelihood and a partial prior on the input

A (semi)deterministic maximum likelihood (DML) approach is presented to solve the joint blind channel identification and blind symbol estimation problem for single-input multiple-output systems. A partial prior on the symbols is incorporated into the criterion which improves the estimation accuracy and brings robustness toward poor channel diversity conditions. At the same time, this method introduces fewer local minima than the use of a full prior (statistical) ML. In the absence of noise, the proposed batch algorithm estimates perfectly the channel and symbols with a finite number of samples. Based on these considerations, an adaptive implementation of this algorithm is proposed. It presents some desirable properties including low complexity, robustness to channel overestimation, and high convergence rate.

Semi-blind channel estimation for OFDM systems via an EM-MAP algorithm

In the OFDM communication context, semi-blind algorithms allow to cope with Doppler effect due to the mobility of wireless systems. For slowly varying channels, the estimation process can be performed on a block of symbols assuming that the channel is constant over the block. This algorithm enhances the performance in terms of channel estimation with the additional advantage of a linear arithmetical complexity. In this paper, we propose an EM-MAP algorithm which takes into account a channel correlation model between the coefficients of the block structure. Simulations results presented in the context of 5 GHz WLANs show that this new algorithm performs better than the EM-block algorithm in the mobile environment.

Achievable Secrecy Rates for the Broadcast Channel With Confidential Message and Finite Constellation Inputs

This paper considers the Broadcast Channel with Confidential Message (BCCM) where the sender attempts to send altogether a common message to two receivers and a confidential message to one of them. The achievable rate regions are derived for the power-constrained Gaussian BCCM with finite input alphabet using various transmission strategies. Namely, time sharing, superposition modulation and superposition coding are used as broadcast strategies. For superposition modulation and superposition coding, the maximal achievable rate regions are obtained by maximizing over both constellation symbol positions and the joint probability distribution. The maximization of the secrecy rate for wiretap channels is also studied as a particular case of the BCCM problem. We compare the considered transmission strategies in terms of percentage gains in achievable rates. We concentrate on the impact of the finite alphabet constraint on achievable rates, and show that this constraint may change well known results obtained in the Gaussian case. We show also that the secrecy constraint can change the shape of the achievable rate region in superposition modulation used in some standards when symbols are equiprobable. On a more practical side, it is shown that a performance close to the optimum can be obtained by strategies with reduced complexity.

On Some Properties of the Mutual Information Between Extrinsics With Application to Iterative Decoding

Iterative decoding is an efficient error-correction tool based on the exchange of extrinsic probabilities between the constituent decoders. In this paper, the properties of the mutual information between the extrinsic LLR at the output of two constituent decoders are analyzed with application to turbo and LDPC codes. This is a bridge between information-theoretic analysis and practical implementations. It is proved here that the mutual information between extrinsics is a lower bound of the mutual information between each extrinsic and the transmitted message. In addition, an efficient online evaluation is provided in the paper with accuracy validated through numerical experiments. As an application, the mutual information between extrinsics is used for designing efficient stopping criterion and error detection rules at the decoder side. Two online methods for the estimation of optimal scaling factor to be applied to the extrinsic LLR are also derived. In contrast with most references, an analytical expression is obtained that does not require estimation of the actual transmitted bits. All results in the paper are derived for Gaussian distributed LLR with independent mean and variance.

Achievable rates optimization for broadcast channels using finite size constellations under transmission constraints

In this paper, maximal achievable rate regions are derived for power-constrained AWGN broadcast channel involving finite constellations and two users. The achievable rate region is studied for various transmission strategies including superposition coding and compared to standard schemes such as time sharing. The maximal achievable rates are obtained by optimizing over both the joint distribution of probability and over the constellation symbol positions. A numerical solution is proposed for solving this non-convex optimization problem. Then, we consider several variations of the same problem by introducing various constraints on the optimization variables. The aim is to evaluate efficiency vs. complexity tradeoffs of several transmission strategies, some of which (the simplest ones) can be found in actual standards. The improvement for each scheme is evaluated in terms of SNR savings for target achievable rates or/and percentage of gain in achievable rates for one user compared to a reference scheme. As an application, two scenarios of coverage areas and user alphabets are considered. This study allows to evaluate with practical criteria the performance improvement brought by more advanced schemes.

A turbo iteration algorithm in 16QAM hierarchical modulation

In the next generation communication protocol “DVB-SH”, it offers a new transmitting scheme based on the turbo code, OFDM modulation and 16QAM hierarchical modulation to increase the flexibility in the information delivery. This scheme is using Hierarchical modulation to enhance the UE (user equipment) performance which is in the center of a sector and also ensure the basic service when UE move to the region of a sector. Hierarchical modulation uses two different bit streams on to different constellation of the constellation map. This scheme ensures two different bit streams have corresponding BER performance and then bring on the flexibility to the transmitting service. The simulation results indicates that in the Rayleigh and Gaussian channel, this scheme can gain a very high BER performance of high priority bit stream, and in the high SNR, it can also gain a high BER performance of low priority bit stream.

On the use of cascade structure to correct impulsive noise in multicarrier systems

We propose a new decoding algorithm based on a cascade structure for impulsive noise correction in multicarrier systems such as orthogonal frequency division multiplexing (OFDM) based systems. This new cascade structure based algorithm has the advantage to lead on one hand to a reduced complexity implementation in an OFDM demodulator and on the other hand to overcome the lacks of other algorithms dedicated for impulsive noise correction. To do so, we start the derivation by investigating closed-form analytical expressions of the a priori probabilities used in hypotheses tests that are necessary for the different steps needed for the execution of the cascade structure based decoding algorithm. Such closed-form expressions for the a priori probabilities, result in efficient setups of the threshold values used for the execution of the decoding algorithm. Furthermore, we show that this cascade structure can be applied to efficiently cancel the impulsive noise in OFDM systems. As the clipping event, present in OFDM systems, can be seen as an additive impulsive noise, we prove that after introducing some minor modifications, we can apply the proposed cascade structure to significantly reduce the peak to average power ratio (PAPR) level in such systems. Simulation results are given to illustrate the usefulness of the proposed algorithm results in practical OFDM based communication systems such as Hiperlan 2.