arXiv subjects

Roberto Lopez-Valcarce

Publications and source records attributed to Roberto Lopez-Valcarce.

4 recordsLinked to original sources

arXiv2019

Hybrid precoding and combining for frequency-selective mmWave MIMO Systems with per-antenna power constraints

Configuring hybrid precoders and combiners is a major challenge to deploy practical mmWave communication systems. Prior work addresses the problem of designing hybrid precoders and combiner, yet focusing on finding solutions under a total transmit power constraint. The design of hybrid precoders and combiners in practical system, is constrained, however, by a per antenna transmit power, since each antenna element in the array is connected to a power amplifier (PA) that has to operate within its linear region. In this paper, we focus on the problem of hybrid precoding and combining with per-antenna power constraints, and under a frequency-selective bandlimited channel model. We first propose an all-digital solution to this problem, and develop a hybrid precoding and combining strategy that aims at matching this solution by minimizing the chordal distance between the all-digital precoders (combiners) and their hybrid approximations. Finally, since minimizing this metric does not guarantee that the final spectral efficiency will be maximized, we optimize the resulting spectral efficiency taking into account the per-antenna power constraints. Simulation results show the effectiveness of our all-digital and hybrid solutions, while emphasizing the differences with respect to the corresponding solution under a total power constraints. As shown in our numerical results, the proposed all-digital solution performs similarly to the case in which a total power constraint is considered. Further, our proposed hybrid solution is also shown to exhibit near-optimum performance, and the influence of different system parameters is also shown, thereby showing the suitability of our proposed framework to deploy practical mmWave MIMO systems.

eess.SP↗

arXiv2017

Distributed Precoding Systems in Multi-Gateway Multibeam Satellites: Regularization and Coarse Beamforming

This paper deals with the problem of beamforming design in a multibeam satellite, which is shared by different groups of terminals -clusters-, each served by an Earth station or gateway. Each gateway precodes the symbols addressed to its respective users; the design follows an MMSE criterion, and a regularization factor judiciously chosen allows to account for the presence of mutually interfering clusters, extending more classical results applicable to one centralized station. More importantly, channel statistics can be used instead of instantaneous channel state information, avoiding the exchange of information among gateways through backhaul links. The on-board satellite beamforming weights are designed to exploit the degrees of freedom of the satellite antennas to minimize the noise impact and the interference to some specific users. On-ground beamforming results are provided as a reference to compare the joint performance of MMSE precoders and on-board beamforming network. A non-adaptive design complements the results and makes them more amenable to practical use by designing a coarse beamforming network.

cs.IT↗

arXiv2017

Learning Power Spectrum Maps from Quantized Power Measurements

Power spectral density (PSD) maps providing the distribution of RF power across space and frequency are constructed using power measurements collected by a network of low-cost sensors. By introducing linear compression and quantization to a small number of bits, sensor measurements can be communicated to the fusion center with minimal bandwidth requirements. Strengths of data- and model-driven approaches are combined to develop estimators capable of incorporating multiple forms of spectral and propagation prior information while fitting the rapid variations of shadow fading across space. To this end, novel nonparametric and semiparametric formulations are investigated. It is shown that PSD maps can be obtained using support vector machine-type solvers. In addition to batch approaches, an online algorithm attuned to real-time operation is developed. Numerical tests assess the performance of the novel algorithms.

cs.IT↗

arXiv2015

Compression Limits for Random Vectors with Linearly Parameterized Second-Order Statistics

The class of complex random vectors whose covariance matrix is linearly parameterized by a basis of Hermitian Toeplitz (HT) matrices is considered, and the maximum compression ratios that preserve all second-order information are derived --- the statistics of the uncompressed vector must be recoverable from a set of linearly compressed observations. This kind of vectors arises naturally when sampling wide-sense stationary random processes and features a number of applications in signal and array processing. Explicit guidelines to design optimal and nearly optimal schemes operating both in a periodic and non-periodic fashion are provided by considering two of the most common linear compression schemes, which we classify as dense or sparse. It is seen that the maximum compression ratios depend on the structure of the HT subspace containing the covariance matrix of the uncompressed observations. Compression patterns attaining these maximum ratios are found for the case without structure as well as for the cases with circulant or banded structure. Universal samplers are also proposed to compress unknown HT subspaces.

math.ST↗