Millimeter‐Wave MIMO Transceivers: Theory, Design and Implementation

Sayeed, A.M.; Brady, John

doi:10.1002/9781119116493.ch10

Cited by 6 publications

(4 citation statements)

References 52 publications

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“…In the future, the theoretical results provided here could be applied to more practical MIMO systems, for example including hybrid precoding and combining [7], [35], [36]. They could allow to determine optimal pilot sequences in this context, as well as to quantify the suboptimality of existing or simpler schemes.…”

Section: Discussionmentioning

confidence: 98%

Channel estimation: unified view of optimal performance and pilot sequences

Magoarou,

Paquelet

2020

Preprint

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Channel estimation is of paramount importance in most communication systems in order to maximize data rate. In modern systems, the possibly large number of transmit/receive antennas and subcarriers makes this task difficult. Several parametric models, either linear or nonlinear, have thus been proposed to ease channel estimation by reducing the dimension of the estimation problem. In this paper, the problem of estimating an object of interest parameterized according to a model, based on noisy complex linear observations is studied. The Cramér-Rao bound (CRB) for this general problem is given, highlighting its key dependency on the introduced variation space. Then, identifiability conditions are given, and the minimal value of the CRB, as well as a general strategy to build minimal length power constrained observation matrices are determined. The results are finally illustrated in a general wideband MIMO context. They allow to retrieve well known previous results, but also to exhibit minimal length optimal pilot sequences in a simple nonlinear physical model setting. Note that the results of this paper are general and could perfectly be used in other applications as well.

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Section: Discussionmentioning

confidence: 98%

Channel estimation: unified view of optimal performance and pilot sequences

Magoarou,

Paquelet

2020

Preprint

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“…However, the problem of beamspace selection in the case of MU transmissions (MU BeamSpace Selection -MBSS) has not yet been studied enough. Existing works have only considered simplified cases when all users had the same channel conditions [19], [23], [24], [25], [26], [27], [28], [29], [30]. For example, in papers [19], [23], and [24], the authors have used data measured via real Massive MIMO testbed [31], [32], but the channel matrix for each UE has been normalized to remove the imbalance in attenuation between users, while in papers [25], [26], [27], [28], [29], and [30], channels for all UEs have been sampled from the same distribution.…”

Section: A Related Workmentioning

confidence: 99%

“…Moreover, the authors have considered all users together trying to maximize total throughput [25], [27], [28], [30] and spectral efficiency [26], [29] or minimize average Bit/Block/Frame Error Rate (BER, BLER, FER, respectively) [19], [23], [24], [33]. At the same time, it has not been analyzed how a certain algorithm affects throughput or BER for each particular UE.…”

Section: A Related Workmentioning

confidence: 99%

“…DFT can be efficiently implemented via Fast Fourier Transform (FFT), therefore, DFT-based methods for beamspace selection are the most popular. For example, they are used in papers [18], [19], [20], [21], [22], [23], [23], [24], [25], [26], [27], [28], [29], [30] and [33]. The main idea of DFT-based beamspace selection for both SU and MU cases is that the full transformation matrix W is a DFT matrix.…”

Section: A Dft-based Beamspace Selectionmentioning

confidence: 99%

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Beamspace Selection in Multi-User Massive MIMO

et al. 2023

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In this paper, we propose new Discrete Fourier Transform (DFT)-based beamspace selection algorithms for Massive Multiple Input, Multiple Output (MIMO) receiver operating in realistic multi-user (MU) scenarios. In practical uplink scenarios, there is a power ratio between signals received from different users that complicates performance analysis in MU cases. Our algorithms are inspired by a proportional fair approach to allocating spatial resources for target users. Thus, we analyze performance in terms of coverage (for low-power users) and capacity (for high-power users) and consider the implementation complexity to highlight feasible algorithms. Simulations with realistic non-line-of-sight scenarios generated by the QuaDRiGa 2.0 demonstrate our methods outperform other DFT-based alternatives, such as the beamspace selection based on the projection power maximization.INDEX TERMS 5G, multi-user massive MIMO, beamspace selection, angular domain processing.

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Sub-array Based Antenna Selection Scheme for Massive MIMO in 5G

Azeem

Ullah

et al. 2019

Communications in Computer and Information Science

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Millimeter‐Wave MIMO Transceivers: Theory, Design and Implementation

Cited by 6 publications

References 52 publications

Channel estimation: unified view of optimal performance and pilot sequences

Channel estimation: unified view of optimal performance and pilot sequences

Beamspace Selection in Multi-User Massive MIMO

Sub-array Based Antenna Selection Scheme for Massive MIMO in 5G

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