Efficient detectors for MIMO-OFDM systems under spatial correlation antenna arrays

Guerra, D.; Fukuda, Rafael Masashi; Kobayashi, Ricardo Tadashi; Abrão, Taufik

doi:10.4218/etrij.2018-0005

Cited by 5 publications

(2 citation statements)

References 21 publications

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“…where 𝑦 𝑘 (𝑛) is NR×1 received vector, 𝐻 𝑘 (𝑛) is NR×NT channel coefficient matrix, 𝑥 𝑘 (𝑛) is NT×1 transmitted vector and 𝑤 𝑘 (𝑛) is NR×1 noise vector with zero mean and variance 𝜎 2 . It is assumed that the number of subcarriers N is sufficiently large to have each subcarrier's channel a flat channel [31]. Space time block coding (STBC) is a powerful scheme of introducing transmit diversity to increasing wireless communications performance.…”

Section: System Modelmentioning

confidence: 99%

“…where 𝑅(𝑖) = 𝐸[𝐻 ̂(𝑛)𝐻 ̂ * (𝑛 − 𝑖)] is the autocorrelation of the LS estimate of the channel. The matrix of the linear system in ( 16) is in the form of Toeplitz matrix and that facilitates the solution of the linear system using the efficient Levinson's algorithm [31]. Figure 2 shows the LPC filter structure, in which the input is the LS estimated channel 𝐻 ̂(𝑛) instead of the received signal as in [15] or the transmitted signal as in [14] The effect of the prediction filter on 𝐻 ̂(𝑛) is the reduction of the noise component 𝑊 ̅ (𝑛).…”

Section: System Modelmentioning

confidence: 99%

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Pilot based channel estimation improvement in orthogonal frequency-division multiplexing systems using linear predictive coding

Saleh Idan,

Al-Haddad

2024

IJECE

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Pilot based least square (LS) channel estimation is a commonly used channel estimation technique in orthogonal frequency-division multiplexing based systems due to its simplicity. However, LS estimation does not handle the noise effect and hence suffers from performance degradation. Since the channel coefficients are correlated in time and hence show a slower variation than the noise, it is possible to encode the channel using linear predictive coding (LPC) without the noise. In this work, the channel is estimated from the pilots using LS estimation and in a second step the channel’s LS estimated is encoded as LPC coefficients to produce an improved channel estimation. The estimation technique is simulated for space-time block coding (STBC) based orthogonal frequency-division multiplexing (OFDM) system and the bit error rate (BER) curves show improvement of the LPC estimation over the LS estimation of the channel.

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Section: System Modelmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

Pilot based channel estimation improvement in orthogonal frequency-division multiplexing systems using linear predictive coding

Saleh Idan,

Al-Haddad

2024

IJECE

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Complexity analysis of FDE receivers for massive MIMO block transmission systems

et al. 2019

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Clustered Double-Scattering Channel Modeling for XL-MIMO With Uniform Arrays

Guerra

Abrão

2022

IEEE Access

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Extra-large multiple-input multiple-output (XL-MIMO) systems reveal themselves as a potential candidate for the sixth generation (6G) of wireless communication systems due to their features. As XL-MIMO has a large antenna array, and, typically, the urban environment is plenty of obstacles and reflectors, the spatial non-stationarities are introduced in the signal received at the base station (BS), which means that only a portion of the antenna array is visible to users; hence, accurately modeling XL-MIMO channels is paramount. Previous works on XL-MIMO channel modeling have adopted the non-stationarities only in a spatial sense, do not considering spatial-time evolution scenarios. Moreover, simplified models with only one set of clusters between the BS and the mobile user (UE) are usually adopted; hence, there is a lack of understanding regarding such channels modeling in the literature. This work proposes and extensively analyzes a double-scattering XL-MIMO channel model, by admitting two types of scattering clusters, one placed at the BS side, and another one located near the UEs. In addition, two distinct antenna array configurations are included in the analysis, the uniform linear and planar arrays (ULA and UPA). We propose a new double-scattering channel model under UPA arrangements, suitable for modeling spatial non-stationarities scenarios in XL-MIMO dynamic environment subject to BS-cluster and UE-cluster correlation, and birth-death channel clusters and scatterers. Numerical results for signal-to-interference-plus-noise ratio (SINR), condition number (CN), and spectral efficiency (SE) performance metrics considering different XL-MIMO channels and system configurations are analyzed via Monte-Carlo simulations, under linear combiners MRC, ZF, and MMSE. Also, we characterize the impact of the number of visible clusters per user, the birth-death rate growth effect on the channel clusters and scatterers, and the favorable propagation effect according to the size of visibility region (VR) overlap. It can be observed that the birth and death processes has a significant impact on the system performance. Under the proposed clustered double-scattering channel modelling, the analyzed XL-MIMO linear receivers presented an SINR degradation when the number of UEs increase substantially around 3 to 4 dB for the MMSE, while the ZF and MRC receivers present a decrease of 1 to 2 dB, approximately, in SINR for the considered dynamic configuration compared with static scenarios. INDEX TERMS uniform linear array (ULA), uniform planar array (UPA), extra large MIMO (XL-MIMO), channel modeling, spatial non-stationary; visibility region, birth and death Poisson process (BDPP). I. INTRODUCTION E XTRA-LARGE multiple-input multiple-output (XL-MIMO) is a promising research direction of multiantenna technology for the sixth-generation (6G) of wireless communication networks [1]-[3]. The main idea of XL-MIMO is to employ a significant number of antennas (10 3 or more) at the base station (BS), which can be widely spread, e.g., on the ...

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Efficient detectors for MIMO-OFDM systems under spatial correlation antenna arrays

Cited by 5 publications

References 21 publications

Pilot based channel estimation improvement in orthogonal frequency-division multiplexing systems using linear predictive coding

Pilot based channel estimation improvement in orthogonal frequency-division multiplexing systems using linear predictive coding

Complexity analysis of FDE receivers for massive MIMO block transmission systems

Clustered Double-Scattering Channel Modeling for XL-MIMO With Uniform Arrays

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