Blind multiuser detection using hidden markov models theory

We present an adaptive algorithm based on the theory of hidden Markov models (HMM) which is capable of jointly detecting the users in a DS-CDMA system. The proposed technique is near-far resistant and completely blind in the sense that no knowledge of the signature sequences, channel state information or training sequences is required for any user. In addition to this, an estimate of the signature of each user convolved with its physical channel impulse response (CIR), and an estimate of the background noise variance are provided once convergence is achieved (as well as estimated data sequences). At this moment, and using that CIR estimate, we can switch to any decision-directed (DD) adaptation scheme.Peer ReviewedPostprint (published version

Performance evaluation of interference cancellation techniques using adaptive antennas

Two array-based algorithms, which jointly exploit or compensate for the spatial and temporal characteristics of the propagation channel, are proposed for intercell interference suppression in UMTS scenarios. The first one is the array extension of the Viterbi algorithm and is referred to as Vector Viterbi algorithm (VVA). The second algorithm, known as filtered training sequence multisensor receiver (FTS-MR), belongs to a class of algorithms in which a narrowband beamformer is placed prior to the MLSE detector. In order to assess performance of the proposed schemes, a set of link-level computer simulations adopting FRAMES' proposal for UMTS air-interface as well as realistic channel models for third generation communication systems is provided, Simulation results reveal gains, in terms of C/I, of 7-10 dB for the VVA with respect to the conventional VA and even higher for the FTS-MR.Peer ReviewedPostprint (published version

Array joint detection for C/TDMA systems in UMTS environments

Two array-based schemes for intracell and intercell interference suppression are proposed. In both cases, the spatial and temporal characteristics of the propagation are jointly exploited by placing a narrowband beamformer prior to the corresponding data detection stage. In the first approach, the filtered training sequence joint detection receiver (FTS-JDR), the beamformer is devoted to exclusively cancel out intercell interference. This way, intracell users can be jointly detected in a MMSE detection block. In contrast, the second algorithm, known as the filtered training sequence multisensor receiver (FTS-MR), aims to attenuate all the interferers in the beamforming stage which allows the user of interest to be detected following a MLSE strategy. In order to assess the performance of the proposed schemes, a set of link-level computer simulations adopting FRAMES' proposal for UMTS air-interface as well as realistic channel models for third generation communication systems is provided. Simulation results indicate that lower BERs can be obtained by concentrating interference cancellation tasks in the beamforming block.Peer ReviewedPostprint (published version

Application of hidden markov models to blind channel estimation and data detection in a gsm environment

In this paper, we present an algorithm based on the Hidden Markov Models (HMM) theory to solve the problem of blind channel estimation and sequence detection in mobile digital communications. The environment in which the algorithm is tested is the Paneuropean Mobile Radio System, also known as GSM. In this system, a large part in each burst is devoted to allocate a training sequence used to obtain a channel estimate. The algorithm presented would not require this sequence, and that would imply an increase of the system capacity. Performance, evaluated for standard test channels, is close to that of non-blind algorithms.Peer ReviewedPostprint (published version

A probabilistic method for blind multiuser detection using array observations

In this paper, a blind algorithm for detecting active users in a DS-CDMA system is presented. This probabilistic algorithm relies on the theory of hidden Markov models (HMM) and is completely blind in the sense that no knowledge of the signature sequences, channel state information or training sequences is required for any user. Additionally, observation through an array of sensors is also considered. Performance is verified via computer simulations, showing the near-far resistance of the analyzed procedure.Peer ReviewedPostprint (published version

Adaptive Beamforming for High Bit Rate Services in the FDD Mode of UTRA

Most time-reference beamforming algorithms suffer from severe beampattern distortion effects when applied to high bit rate services in WCDMA, causing serious performance degradation in terms of output BER, especially at high input SINR levels. These shortcomings are essentially caused by the uplink multiplexing of the traffic channel, which is seen by the base station as a powerful interfering source coming from the direction of arrival of the desired user. In this paper, a semi-blind beamforming technique is proposed as a valid solution to overcome this effect. The suggested scheme resorts to a conditional maximum likelihood approach to the underlying estimation problem and is designed to operate in an iterative fashion.Peer ReviewedPostprint (published version

Signal Processing-Assisted Protocols and Algorithms for Cooperating Objects and Wireless Sensor Networks

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Reconstruction of correlated sources with energy harvesting constraints

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we investigate how to minimize the distortion in the reconstruction of correlated sources.We consider a communication scenario where a sensor node is capable of harvesting energy from the environment and where the Fusion Center (FC), in order to exploit correlation, uses past observations as side information for decoding. We provide a convex formulation of the problem and derive the optimal transmission policies (i.e., power and rate allocation). We also propose an iterative procedure based on the subgradient method by means of which a solution can be iteratively found. Interestingly, each iteration entails the interaction (coupling) of a directional water-filling and a reverse water-filling schemes. Numerical results are provided in order to illustrate the impact of correlation in the resulting transmission policies.Peer ReviewedPostprint (author’s final draft

On the impact of correlated sampling processes in WSNs with energy-neutral operation

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we consider a communication scenario where multiple EH sensor nodes collect correlated measurements of an underlying random field. The nodes operate in an energy-neutral manner (i.e. energy is used as soon as it is harvested) and, hence, the energy-harvesting and sampling processes at the sensor nodes become inter-twined, random and spatially correlated. Under some mild assumptions, we derive the multidimensional linear filter which minimizes the mean square error in the reconstructed measurements at the Fusion Center (FC). We also analyze the impact of correlated and random sampling processes in the resulting distortion and, in order to gain some insight, we particularize the analysis to the case of fully correlated spatial fields and with an asymptotically large number of sensor nodes.Peer ReviewedPostprint (author's final draft