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José P. González-Coma

Publications and source records attributed to José P. González-Coma.

9 recordsLinked to original sources

Hybrid Multiport Receivers for Slow Fluid Antenna Multiple Access

We propose a novel receiver architecture that preserves the performance benefits of multiport selection in fluid-antenna systems while requiring only a very small number of radio-frequency (RF) chains. The resulting fluid-antenna hybrid multiport (FAHM) receiver effectively decouples port selection from signal combining by integrating a low-complexity analog combining network similar to those used in conventional hybrid multiantenna designs. We develop a stopping criterion to determine the number of selected ports, which limits the performance loss associated with port selection, and then design the hybrid combiner for a given RF-chain budget. The FAHM architecture is evaluated in a multiuser set-up operating under slow fluid-antenna multiple access (FAMA). In this scenario, a FAHM implementation with only 2 RF chains showcases a performance comparable to a fully-digital conventional multiport scheme with a much larger number of RF chains. Additionally, the proposed receiver architecture attains over 60% reduction in computational burden when integrated with a novel efficient implementation of the state-of-the-art generalized-eigenvector port-selection method.

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Slow Fluid Antenna Multiple Access with Multiport Receivers

We investigate whether equipping fluid-antenna (FA) receivers with multiple ($L>1$) radiofrequency (RF) chains can improve the performance of the slow fluid-antenna multiple access (FAMA) technique, which enables open-loop connectivity with channel state information (CSI) available only at the receiver side. We analyze the case of slow-FAMA users equipped with multiport receivers, so that $L$ ports of the FA are selected and combined to reduce interference. We show that a joint design of the port selection matrix and the combining vector at each receiver yields significant performance gains over reference schemes, demonstrating the potential of multiport reception in FA systems with a limited number of RF chains.

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User Selection in Near-Field Gigantic MIMO Systems with Modular Arrays

Modular Arrays (MAs) are a promising architecture to enable multi-user communications in next-generation multiple-input multiple-output (MIMO) systems based on extra-large (XL) or gigantic MIMO (gMIMO) deployments, trading off improved spatial resolution with characteristic interference patterns associated with grating lobes. In this work, we analyze whether MAs can outperform conventional collocated deployments, in terms of achievable sum-spectral efficiency (SE) and served users in a multi-user downlink set-up. First, we provide a rigorous analytical characterization of the inter-user interference for modular gMIMO systems operating in the near field. Then, we leverage these results to optimize the user selection and precoding mechanisms, designing two algorithms that largely outperform existing alternatives in the literature, with different algorithmic complexities. Results show that the proposed algorithms yield over 70% improvements in achievable sum-spectral efficiencies compared to the state of the art. We also illustrate how MAs allows us to serve a larger number of users thanks to their improved spatial resolution, compared to the collocated counterpart.

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A Rank-Constrained Coordinate Ascent Approach to Hybrid Precoding for the Downlink of Wideband Massive (MIMO) Systems

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 precoder 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 additional problem formulation to determine an appropriate power allocation policy according to the rank constraint is also provided. 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

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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Low-Complexity Distance-Based Scheduling for Multi-User XL-MIMO Systems

We introduce DBS, a new technique for user selection in downlink multi-user communications with extra-large (XL) antenna arrays. DBS categorizes users according to their equivalent distance to the antenna array. Such categorization effectively accounts for inter-user interference while largely reducing the computational burden. Results show that (i) DBS achieves the same performance as the reference zero-forcing beamforming scheme with a lower complexity; (ii) a simplified version of DBS achieves a similar performance when realistic spherical-wavefront (SW) propagation features are considered; (iii) SW propagation brings additional degrees of freedom, which allows for increasing the number of served users.

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Hybrid LISA for Wideband Multiuser Millimeter Wave Communication Systems under Beam Squint

This work jointly addresses user scheduling and precoder/combiner design in the downlink of a wideband millimeter wave (mmWave) communications system. We consider Orthogonal Frequency Division Multiplexing (OFDM) modulation to overcome channel frequency selectivity and obtain a number of equivalent narrowband channels. Hence, the main challenge is that the analog preprocessing network is frequency flat and common to all the users at the transmitter side. Moreover, the effect of the signal bandwidth over the Uniform Linear Array (ULA) steering vectors has to be taken into account to design the hybrid precoders and combiners. The proposed algorithmic solution is based on Linear Successive Allocation (LISA), which greedily allocates streams to different users and computes the corresponding precoders and combiners. By taking into account the rank limitations imposed by the hardware at transmission and reception, the performance loss in terms of achievable sum rate for the hybrid approach is negligible. Numerical experiments show that the proposed method exhibits excellent performance with reasonable computational complexity.

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QoS Constrained Power Minimization in the Multiple Stream MIMO Broadcast Channel

This work addresses the design of optimal linear transmit filters for the Multiple Input-Multiple Output (MIMO) Broadcast Channel (BC) when several spatial streams are allocated to each user.We also consider that the Channel State Information (CSI) is perfect at the receivers but is only partial at the transmitter. A statistical model for the partial CSI is assumed and exploited for the filter design. Similarly to the single-stream per user case, the problem is solved via Mean Square Error (MSE) dualities and interference functions. However, including more streams per user involves an additional complexity level since we must determine how to distribute the per-user rates among the streams. Such problem is solved using a projected gradient algorithm.

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QoS Constrained Power Minimization in the MISO Broadcast Channel with Imperfect CSI

We consider the design of linear precoders and receivers in a Multiple-Input Single-Output (MISO) Broadcast Channel (BC). We aim at minimizing the transmit power while fullfiling a set of per-user Quality-of-Service (QoS) constraints expressed in terms of per-user average rate requirements. The Channel State Information (CSI) is assumed to be perfectly known at the receivers but only partially at the transmitter. To solve the problem we transform the QoS constraints into Minimum Mean Square Error (MMSE) constraints. We then leverage the MSE duality between the BC and the Multiple Access Channel (MAC), as well as standard interference functions in the dual MAC, to perform power minimization by means of an Alternating Optimization (AO) algorithm. Problem feasibility is also studied to determine whether the QoS constraints can be fulfilled or not. Finally, we present an algorithm to balance the average rates and manage situations that may be unfeasible or lead to an unacceptably high transmit power.

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