Browsing by Author "Fresnedo, Óscar"

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    A rank-constrained coordinate ascent approach to hybrid precoding for the downlink of wideband massive MIMO systems
    (2023-02-01) González-Coma, José P.; Fresnedo, Óscar; Castedo, Luis
    An innovative approach to hybrid analog-digital precoding for the downlink of wideband massive MIMO systems is developed. The proposed solution, termed Rank-Constrained Coordinate Ascent (RCCA), starts seeking the full-digital pre coder that maximizes the achievable sum-rate over all the frequency subcarriers while constraining the rank of the overall transmit covariance matrix. The frequency-flat constraint on the analog part of the hybrid precoder and the non-convex nature of the rank constraint are circumvented by transforming the original problem into a more suitable one, where a convenient structure for the transmit covariance matrix is imposed. Such structure makes the resulting full-digital precoder particularly adequate for its posterior analog-digital factorization. An addi tional problem formulation to determine an appropriate power allocation policy according to the rank constraint is also pro vided. The numerical results show that the proposed method outperforms baseline solutions even for practical scenarios with high spatial diversity.
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    Alternating Minimization for Wideband Multiuser IRS-aided MIMO Systems under Imperfect CSI
    (IEEE, 2023-11) Pérez-Adán, Darian; Joham, Michael; Fresnedo, Óscar; González-Coma, José P.; Castedo, Luis; Utschick, Wolfgang
    This work focuses on wideband intelligent reflecting surface (IRS)-aided multiuser MIMO systems. One of the major challenges of this scenario is the joint design of the frequency dependent base station (BS) precoder and user filters, and the IRS phase-shift matrix which is frequency flat and common to all the users. In addition, we consider that the channel state information (CSI) is imperfect at both the transmitter and the receivers. A statistical model for the imperfect CSI is developed and exploited for the system design. A minimum mean square error (MMSE) approach is followed to determine the IRS phase-shift matrix, the transmit precoders, and the receiving filters. The broadcast (BC)-multiple access channel (MAC) duality is used to solve the optimization problem following an alternating minimization approach. Numerical results show that the proposed approach leads to substantial performance gains with respect to baseline strategies that neglect the inter-user interference and do not optimize the IRS phase-shift matrix. Further performance gains are obtained when incorporating into the system design the statistical information of the channel estimation errors.
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    Design of Linear Precoders for Correlated Sources in MIMO Multiple Access Channels
    (IEEE, 2018) Suárez-Pascal, Pedro; González-Coma, José P.; Fresnedo, Óscar; Castedo, Luis
    This work focuses on distributed linear precod ing when users transmit correlated information over a fading Multiple-Input and Multiple-Output Multiple Access Channel. Precoders are optimized in order to minimize the sum-Mean Square Error (MSE) between the source and the estimated symbols. When sources are correlated, minimizing the sum-MSE results in a non-convex optimization problem. Precoders for an arbitrary number of users and transmit and receive antennas are thus obtained via a projected steepest-descent algorithm and a low-complexity heuristic approach. For the more restrictive case of two single-antenna users, a closed-form expression for the minimum sum-MSE precoders is derived. Moreover, for the scenario with a single receive antenna and any number of users, a solution is obtained by means of a semidefinite relaxation. Finally, we also consider precoding schemes where the precoders are decomposed into complex scalars and unit norm vectors. Simulation results show a significant improvement when source correlation is exploited at precoding, especially for low SNRs and when the number of receive antennas is lower than the number of transmitting nodes.