Antonio Pascual Iserte

Joint beamforming strategies in OFDM-MIMO systems

Orthogonal Frequency Division Multiplexing (OFDM) has been recently established for several systems such as HIPERLAN/2 and Digital Video and Audio Broadcasting. The success of this modulation is due to the easy implementati9n of the modulator and demodulator, including the equalization process. Moreover, in last years also increasing interest has been put on the study of Multi-Input-Multi-Output (MIMO) channels, based on the use of arrays of antennas at both the transmitter and the receiver. In this paper we propose two new and low computational cost joint beamforming strategies for communication systems that combine OFDM and MIMO channels. An asymptotic analysis of the proposed methods is carried out, providing a complete comparative study among other classical strategies. To demonstrate the potential of the proposed techniques, we present MonteCarlo simulation results of the system BER and make comparisons with other methods.

Convex optimization theory applied to joint beamforming design in multicarrier MIMO channels

This paper addresses the joint design of transmit and receive beamvectors for a multicarrier MIMO channel within the general and powerful framework of convex optimization theory. From this perspective, a great span of design criteria can be easily accommodated and efficiently solved even though closed-form expressions may not be available. Among other criteria, we consider the minimization of the average bit error rate (BER) and also of the maximum BER among all carriers for a given signal constellation. We show how to include additional constraints to control the peak-to-average ratio (PAR) in the system design.

Iterative algorithm for the estimation of distributed sources localization parameters

We present a novel algorithm for the estimation of the direction of arrival and angular distribution parameters of sources that, as a result from the scattering effects, cannot be considered as punctual. The algorithm is iterative and is based on the maximization of the likelihood function associated to the received snapshots at the antenna array (ML). It is proposed a computationally efficient method for estimating the localization and angular distribution parameters of more than one source transmitting at the same frequency in a noisy environment. This algorithm solves the problem of the joint maximization in the case of two sources by formulating two new problems of a single-source ML.

Robust power allocation for minimum BER in a SISO-OFDM system

In this paper we address the problem of the design of a power allocation strategy for an orthogonal frequency division multiplexing (OFDM) system. We assume no spatial diversity at the transmitter and receiver, that is, a single-input-single-output (SISO) channel is considered. The goal is to allocate all the available power at the transmitter among the different carriers according to a minimum mean bit error rate (BER) criterion. When designing this strategy, we assume that channel state information (CSI) is available at the transmitter. Two different approaches are taken. The first one considers that the channel estimates are perfect, whereas the second approach assumes that there is some estimation error, and therefore, this approach is robust in nature. Finally, we propose an efficient algorithm for computing the power allocated to the carriers for both approaches, and show some simulation results in order to compare them.

Energy-latency trade-off for multiuser wireless computation offloading

This paper addresses the trade-off between latency and energy consumption in wireless application offloading in a multiuser set-up. The advantages of carrying out offloading versus executing an application locally at the user terminal depend on multiple parameters. This paper evaluates the impact that the transmission rate and the load of the system have on the quality of service experienced by the users as well as on the energy saving that the users get from doing offloading. Based on this evaluation, the paper proposes a method to select the uplink data rate that minimizes the latency experienced by the user given a target energy saving with respect to the case of no offloading. The result depends on the channels conditions, the system load, the application parameters, and the energy consumption features of the terminal. The method is presented firstly for flat fading channels and secondly for non-flat fading channels.

Energy-efficient resource allocation techniques for battery management with energy harvesting nodes: A theoretical approach

This paper addresses the problem of radio resource allocation in a multi-user broadcast downlink flat-fading channel, where the receiving nodes are considered to be battery-powered devices provided with energy harvesting sources. Models for the energy consumption of the RF and decoding stages are discussed and included explicitly in the design of the resource allocation strategy. The allocation is considered as a theoretical approach, using the information theoretic rate given by Shannons formula. Bandwidth, power, and data rate are optimized considering energy-related constraints related to the status of the batteries in order to increase the lifetime of the users and, thus, the global network lifetime. Simulation results show that not only the usage of battery is improved when compared with other traditional allocation policies, but also the average data rate achieved by the network nodes is increased.This paper addresses the problem of radio resource allocation in a multi-user broadcast downlink flat-fading channel, where the receiving nodes are considered to be battery-powered devices provided with energy harvesting sources. Models for the energy consumption of the RF and decoding stages are discussed and included explicitly in the design of the resource allocation strategy. The allocation is considered as a theoretical approach, using the information theoretic rate given by Shannon’s formula. Bandwidth, power, and data rate are optimized considering energy-related constraints related to the status of the batteries in order to increase the lifetime of the users and, thus, the global network lifetime. Simulation results show that not only the usage of battery is improved when compared with other traditional allocation policies, but also the average data rate achieved by the network nodes is increased.