Lionel Husson

A new method for reducing the power consumption of portable handsets in TDMA mobile systems: conditional equalization

In time-division multiple-access (TDMA) systems, the autonomy of portable handsets is a major constraint. We propose a new method, conditional equalization, which minimizes the power consumption due to equalization by equalizing only when it is most needed. At each time slot, the receiver estimates the need for equalization with a deterministic criterion. The proposed criteria use thresholds, chosen to provide a compromise between loss in performance and percentage of saved equalization. The performance of our method is theoretically analyzed for two-path Rayleigh fading channels and simulated for the recommended COST 207 channels. Conditional equalization can ensure a degradation in the average signal-to-noise ratio (SNR), providing a fixed bit error rate (BER with an average SNR=9 dB with systematic equalization), of less than 0.5 dB while providing a gain of 43% spared equalization for bad urban (BU), 62% for hilly terrain (HT), 79% for typical urban (TU), and 98% for rural area (RA) models, respectively. Conditional equalization is shown to greatly improve the autonomy of the receiver by drastically reducing the power consumption due to equalization, without a noticeable loss in the performance.

A novel approach to model the land mobile satellite channel through reversible jump markov chain monte carlo technique

A key issue in the design of a mobile satellite communication system is an adequate knowledge of the statistical behavior of the propagation channel. To achieve this goal, the development of very accurate models plays a very important role. In contrast to traditional multi-state Markov chain based models, the novel approach proposed in this paper makes no prior assumptions on the number of states or on the statistical distributions characterizing each state. The sequence of channel states is blindly estimated using a Reversible Jump Monte Carlo Markov Chain algorithm.

Efficient evaluation of voice quality in GERAN (GSM EDGE Radio Access Network)

The transport of multimedia application is now a key feature of the future radio access networks. The evolution of GSM networks is also able in principle to take benefit from end-to-end transfer of such applications. However, careful attention has to be taken regarding the quality perceived by the end user. Indeed, for voice services, mobile subscribers are familiar with a given quality. The introduction of IP services should not decrease this quality. Besides, the introduction of such feature on the radio links should also enable the operators to increase their network capacity. In this context, this paper analyses the perceived voice quality when voice frames are transported on existing packet radio bearers of GSM/EDGE Radio Access Networks. In this situation, the benefit for the operator should be maximal. The quality is evaluated with an objective method that relies on comparison of reference speech sequence with the same sequence that is passed through GERAN radio links. This methodology of evaluation if by far more consistent than simply considering radio link level performance like the bit error rate.

Autonomous Decision Making Process for the Dynamic Reconfiguration of Cognitive Radios

The aim of this paper is to present a generic cognitive framework for autonomous decision making with regard to multiple, possibly conflicting, operational objectives in the face of a time-varying environment. The framework is based on the definition of two scales introducing order relationships between the configurations that help the reasoning and learning processes. The resulting cognitive engine learns from scratch to identify the optimal configuration with regard to the design objectives given the current radio environment. The proposed approach is validated on a case of cognitive waveform design voluntarily kept simple for illustration purpose. The possibility of extending this framework to more complex problems is also discussed.

Performance of adaptive MC-CDMA in HiperLAN/2++

The study presented in this paper is twofold. First, the physical layer performance of an adaptive MC-CDMA, considering the parameters of two wireless LAN (WLAN) HiperLAN/2, and IEEE 802.11a, are presented. Secondly, we explain singular value decomposition (SVD) based approach to demonstrate the effective utilization of coherence bandwidth of ETSI BRAN channels through an orthogonal variable spreading factor (OVSF) MC-CDMA. In addition, the advantage of supplementary diversity obtained by the utilization of a random frequency hopping (FH) for interleaving the sub-carriers carrying chip codes is explained. Once again, the SVD is employed to illustrate this feature related to increased frequency diversity of the channel.

Scalable Multi-State Markovian Modeling of Time Series of Received Power from Measurements of Mobile Satellite Transmissions in the L-Band

In a context of mobile radio transmissions a statistical model of propagation channels is needed in order to evaluate the performance of the link. Many models involve an underlying Markov chain where the number of states and the associated probability law are a priori unknown. We propose a method to extract these parameters from measurements of instantaneous received power. It is applied to model the channel in the case of downlink transmissions in the L-band, from a non-geostationary satellite to a receiver on Earth in various terrestrial environments. The results are displayed for two categories of receivers, corresponding to vehicular and pedestrian users, and reveal difference between both models.

SAT04-2: Accurate and Novel Modeling of the Land Mobile Satellite Channel using Reversible Jump Markov Chain Monte Carlo Technique

A key issue in the design of a mobile satellite communication system is an adequate knowledge of the statistical behavior of the propagation channel. To achieve this goal, the development of very accurate models plays a very important role. In contrast to traditional multi-state Markov chain based models, the novel approach proposed in this paper makes no prior assumptions on the number of states or on the statistical distributions characterizing each state. The sequence of channel states is blindly estimated using a reversible jump Monte Carlo Markov chain algorithm.

WLC13-6: Receiver Directed Adaptation of Multicode CDMA Transmission for Frequency-Selective Rayleigh Fading Channels

Future wireless communication systems require highly efficient use of radio parameters. Adaptability to changing environment conditions and to service application requirements is of great importance for the design of link adaptation. In this paper, we consider the joint optimization of CDMA radio parameters to maximize the instantaneous throughput for a bit error rate (BER) target. In order to increase the granularity of the adaptation in CDMA systems, combined adaptive multicode and multilevel modulation is employed. We show that this combined adaptation additionally enhances throughput in frequency-selective environments. Optimized link adaptation requires the knowledge of the channel impulse response as well as the used receiver model. Therefore, we assume that the receiver user equipment reports to the transmitter the optimum transport format maximizing the instantaneous bit rate so that a BER target is met. Joint optimization of radio parameters is based on analytical receiver performance evaluation. We assume single user multicode CDMA transmission during each time-slot. The available throughput is evaluated over frequency-selective channels for RAKE receivers and for more advanced equalizers such as joint multi-code block linear equalizers.

Algorithms for BER-Constrained Variable-Length Equalizers driven by Channel Response Knowledge over Frequency-Selective Radio Channel

In mobile radio systems, transmission conditions actually encounter large variations depending on the effective environmental configurations. Training sequences are periodically inserted into the transmitted messages so that the receiver can estimate the channel response. Based on this knowledge, we study the problem of adapting the equalizer filter length to a given channel impulse response under bit error rate constraint. In this paper, both linear equalizer (LE) and decision feedback equalizer (DFE) are studied. Accurate control of the equalizer length can improve the systems performance while reducing the handset power consumption or reducing software load in a software radio context. Besides, in a multi-service system, it allows to manage variable quality of service requirements. Optimal and suboptimal criteria for determining the equalizer length are discussed in order to optimize the overall complexity of the receiver including training phase and decoding phases.

New optimal hard decoding of convolutional codes with reduced complexity

It is well known that convolutional codes can be optimally decoded by the Viterbi algorithm (VA). We propose an optimal hard decoding technique where the VA is applied to identify the error vector rather than the information message. In this paper, we show that, with this type of decoding, the exhaustive computation of a vast majority of state-to-state iterations is unnecessary. Hence, under certain channel conditions, optimum performance is achievable with a sensible reduction in complexity.