Transmit Signal Design for MIMO Radar and Massive MIMO Channel Estimation

The widespread availability of antenna arrays and the capability to independently control signal emissions from each antenna make transmit signal design increasingly important for radar and wireless communication systems. In the rst part of this work, we develop the framework for a MIMO radar transmit scheme which trades o waveform diversity for beampattern directivity. Time-division beamforming consists of a linear precoder that provides direct control of the transmit beampattern and is able to form multiple transmit beams in a single pulse. The MIMO receive ambiguity function, which incorporates the receiver structure, reveals a space and delay-Doppler separability that emphasizes the importance of the transmit-receive beampattern and single-input single-output (SISO) ambiguity function. The second part of this work focuses on channel estimation for massive MIMO systems. As the size of arrays increase, conventional channel estimation techniques no longer remain practical. In current systems, training sequences probe wireless channels in orthogonal directions to obtain channel state information for block fading channels. The training overhead becomes signicant as the number of transmit antennas increases, thereby creating a need for alternative channel estimation techniques. In this work, we relax the orthogonal restriction on the sounding vectors and introduce a feedback channel to enable closed-loop sounding vector design. A probability of misalignment framework is introduced, which provides a measure to sequentially design sounding vectors

Large System Analysis of Base Station Cooperation for Power Minimization

This work focuses on a large-scale multi-cell multi-user MIMO system in which $L$ base stations (BSs) of $N$ antennas each communicate with $K$ single-antenna user equipments. We consider the design of the linear precoder that minimizes the total power consumption while ensuring target user rates. Three configurations with different degrees of cooperation among BSs are considered: the coordinated beamforming scheme (only channel state information is shared among BSs), the coordinated multipoint MIMO processing technology or network MIMO (channel state and data cooperation), and a single cell beamforming scheme (only local channel state information is used for beamforming while channel state cooperation is needed for power allocation). The analysis is conducted assuming that $N$ and $K$ grow large with a non trivial ratio $K/N$ and imperfect channel state information (modeled by the generic Gauss-Markov formulation form) is available at the BSs. Tools of random matrix theory are used to compute, in explicit form, deterministic approximations for: (i) the parameters of the optimal precoder; (ii) the powers needed to ensure target rates; and (iii) the total transmit power. These results are instrumental to get further insight into the structure of the optimal precoders and also to reduce the implementation complexity in large-scale networks. Numerical results are used to validate the asymptotic analysis in the finite system regime and to make comparisons among the different configurations.Comment: 32 pages, 6 figures, to appear IEEE Trans. Wireless Commun. A preliminary version of this paper was presented at the IEEE Global Communication Conference, San Diego, USA, Dec. 201

Scalable cell-free massive MIMO networks with LEO satellite support

This paper presents an integrated network architecture combining a cell-free massive multiple-input multiple-output (CF-M-MIMO) terrestrial layout with a low Earth orbit satellite segment where the scalability of the terrestrial segment is taken into account. The main purpose of such an integrated scheme is to transfer to the satellite segment those users that somehow limit the performance of the terrestrial network. Towards this end, a correspondingly scalable technique is proposed to govern the ground-to-satellite user diversion that can be tuned to different performance metrics. In particular, in this work the proposed technique is configured to result in an heuristic that improves the minimum per-user rate and the sum-rate of the overall network. Simulation results serve to identify under which conditions the satellite segment can become an attractive solution to enhance users’ performance. Generally speaking, although the availability of the satellite segment always leads to an improvement of users’ rates, it is in those cases where the terrestrial CF-M-MIMO network exhibits low densification traits that the satellite backup becomes crucial.This work was supported in part by the Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación (MCIN/AEI/10.13039/501100011033) through the R+D+i Project under Grant PID2020-115323RB-C32 and Grant PID2020-115323RB-C31; and in part by the Centre Tecnológic de Telecomunicacions de Catalunya Researchers through the Grant from the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-NextGenerationEU under Grant UNICO-5G I+D/AROMA3D-Hybrid TSI-063000-2021-71.Peer ReviewedPostprint (published version

User selection for massive MIMO under line-of-sight propagation

This paper provides a review of user selection algorithms for massive multiple-input multiple-output (MIMO) systems under the line-of-sight (LoS) propagation model. Although the LoS propagation is extremely important to some promising technologies, like in millimeter-wave communications, massive MIMO systems are rarely studied under this propagation model. This paper fills this gap by providing a comprehensive study encompassing several user selection algorithms, different linear precoders and simulation setups, and also considers the effect of partial channel state information (CSI). One important result is the existence of practical cases in which the LoS propagation model may lead to significant levels of interference among users within a cell; these cases are not satisfactorily addressed by the existing user selection algorithms. Motivated by this issue, a new user selection algorithm based on inter-channel interference (ICI) called ICI-based selection (ICIBS) is proposed. Unlike other techniques, the ICIBS accounts for the ICI in a global manner, thus yielding better results, especially in cases where there are many users interfering with each other. In such scenarios, simulation results show that when compared to the competing algorithms, the proposed approach provided an improvement of at least 10.9% in the maximum throughput and 7.7% in the 95%-probability throughput when half of the users were selected