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Next generation communication systems require accurate beam alignment to counteract the impairments that characterize propagation in high-frequency bands. The overhead of the pilot sequences required to select the best beam pair is prohibitive when codebooks contain a large number of beams, as is the case in practice. To remedy this issue, some schemes exploit information about the user location to predict the best beam pair. However, these schemes (i) involve no measurements whatsoever, which generally results in a highly suboptimal predicted beam, and (ii) are not robust to localization errors. To address these limitations, this paper builds upon the notion of radio map to develop two algorithms that attain a balance between the quality of the obtained beam pair and measurement overhead. The proposed algorithms predict the received power corresponding to each pair and measure just the Q pairs with highest prediction. While the first algorithm targets simplicity, the second one relies on a Bayesian approach to endow the prediction process with robustness to localization error. The performance of both algorithms is shown to widely outperform existing methods using ray-tracing data.

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.

We propose a novel mode of operation for Amplify-and-Forward relays in which the spectra of the relay input and output signals partially overlap. This partial-duplex relaying mode encompasses half-duplex and full-duplex as particular cases. By viewing the partial-duplex relay as a bandwidth-preserving Linear Periodic Time-Varying system, an analysis of the spectral efficiency in the presence of self-interference is developed. In contrast with previous works, self-interference is regarded as a useful information-bearing component rather than simply assimilated to noise. This approach reveals that previous results regarding the impact of self-interference on (full-duplex) relay performance are overly pessimistic. Based on a frequency-domain interpretation of the effect of self-interference, a number of suboptimal decoding architectures at the destination node are also discussed. It is found that the partial-duplex relaying mode may provide an attractive tradeoff between spectral efficiency and receiver complexity., Comment: Submitted to IEEE Transactions on Wireless Communications

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., Comment: Submitted to IEEE Transactions on Wireless Communications

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., Comment: Submitted Jun. 2016

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., Comment: 15 pages, 2 figures, 1 table, submitted to IEEE Transactions on Information Theory on Nov. 4, 2013