Bounds for Eigenvalues of Spatial Correlation Matrices With the Exponential Model in MIMO Systems

Lim, Han-Cheol; Jang, Yeonsoo; Yoon, Dongweon

doi:10.1109/twc.2016.2641419

Cited by 45 publications

(12 citation statements)

References 33 publications

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“…H ). Following [31], [35], [36], we adopt the exponential correlation model, where the ( , )-th entry [R] , of the correlation matrix R is given by (39) where 0 ≤ BS , H ≤ 1 denote the correlation coefficients between adjacent antennas at the BS and between adjacent antennas at homes, respectively; ( ) and ℎ( ) are the vertical and horizontal indexes of the -th antenna of the UPA. For the BS we set BS = 0.4 [31].…”

Section: A System and Channel Settingsmentioning

confidence: 99%

Planning 5G Networks for Rural Fixed Wireless Access

Lappalainen,

Zhang,

Rosenberg

2021

Preprint

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We study the planning of a rural 5G multi-user massive MIMO fixed wireless access system to offer fixed broadband service to homes. Specifically, we aim to determine the user limit, i.e., the maximum number of homes that can simultaneously receive target minimum bit rates (MBRs) on the downlink (DL) and on the uplink (UL) given a set of network resources and a cell radius. To compute that limit, we must understand how resources should be shared between the DL and UL and how user and stream selection, precoding and combining, and power distribution should be performed. We use block diagonalization and propose a static grouping strategy that organizes homes into fixed groups (of possibly different sizes) in the DL and UL; then we develop a simple approach to compute the user limit that we validate numerically. We study the impact of group size and show that smaller groups yield larger user limits in a 3.5 GHz band. We show how the user limit at different cell radii is impacted by the system bandwidth, the number of antennas at the BS and homes, the BS power, and the DL and UL MBRs. Lastly, we offer insights into how the network could be operated.

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Section: A System and Channel Settingsmentioning

confidence: 99%

Planning 5G Networks for Rural Fixed Wireless Access

Lappalainen,

Zhang,

Rosenberg

2021

Preprint

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“…Nevertheless, it did not demonstrate some statistical characteristics of this model and only a ULA arrangement was considered. The derivation of superior and inferior analytical bounds for the eigenvalues generated by the exponential correlation model is treated in the works of Choi and Love and Lim et al However, the authors did not discuss the influence of this model over M‐MIMO scenarios. A more robust analytical study behind the eigenstructure of the exponential correlation matrix is carried out in the work of Mallik .…”

Section: Introductionmentioning

confidence: 99%

Exponential spatial correlation with large‐scale fading variations in massive MIMO channel estimation

Rodrigues

Marinello

Abrão

2019

Trans Emerging Tel Tech

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To provide the vast exploitation of the large number of antennas on massive multiple‐input–multiple‐output (M‐MIMO), it is crucial to know as accurately as possible the channel state information in the base station. This knowledge is canonically acquired through channel estimation procedures conducted after a pilot signaling phase, which adopts the widely accepted time‐division duplex scheme. However, the quality of channel estimation is very impacted either by pilot contamination or by spatial correlation of the channels. There are several models that strive to match the spatial correlation in M‐MIMO channels, the exponential correlation model being one of these. To observe how the channel estimation and pilot contamination are affected by this correlated fading model, this work proposes to investigate an M‐MIMO scenario applying the standard minimum mean square error channel estimation approach over uniform linear arrays and uniform planar arrays (ULAs and UPAs, respectively) of antennas. Moreover, the elements of the array are considered to contribute unequally on the communication, owing to large‐scale fading variations over the array. Thus, it was perceived that the spatially correlated channels generated by this combined model offer a reduction of pilot contamination, consequently the estimation quality is improved. The UPA acquired better results regarding pilot contamination since it has been demonstrated that this type of array generates stronger levels of spatial correlation than the ULA. In contrast to the favorable results in channel estimation, the channel hardening effect was impaired by the spatially correlated channels, where the UPA imposes the worst performance of this effect for the discussed model.

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Section: Introductionmentioning

confidence: 99%

Exponential Spatial Correlation with Large-Scale Fading Variations in Massive MIMO Channel Estimation

Rodrigues¹,

Marinello²,

Abrão³

2019

Preprint

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To provide the vast exploitation of the large number of antennas on massive multiple-input-multipleoutput (M-MIMO), it is crucial to know as accurately as possible the channel state information in the base station. This knowledge is canonically acquired through channel estimation procedures conducted after a pilot signaling phase, which adopts the widely accepted time-division duplex scheme. However, the quality of channel estimation is very impacted either by pilot contamination or by spatial correlation of the channels.There are several models that strive to match the spatial correlation in M-MIMO channels, the exponential correlation model being one of these. To observe how the channel estimation and pilot contamination are affected by this correlated fading model, this work proposes to investigate an M-MIMO scenario applying the standard minimum mean square error channel estimation approach over uniform linear arrays and uniform planar arrays (ULAs and UPAs, respectively) of antennas. Moreover, the elements of the array are considered to contribute unequally on the communication, owing to large-scale fading variations over the array. Thus, it was perceived that the spatially correlated channels generated by this combined model offer a reduction of pilot contamination, consequently the estimation quality is improved. The UPA acquired better results regarding pilot contamination since it has been demonstrated that this type of array generates stronger levels of spatial correlation than the ULA. In contrast to the favorable results in channel estimation, the channel hardening effect was impaired by the spatially correlated channels, where the UPA imposes the worst performance of this effect for the discussed model.

show abstract

Bounds for Eigenvalues of Spatial Correlation Matrices With the Exponential Model in MIMO Systems

Cited by 45 publications

References 33 publications

Planning 5G Networks for Rural Fixed Wireless Access

Planning 5G Networks for Rural Fixed Wireless Access

Exponential spatial correlation with large‐scale fading variations in massive MIMO channel estimation

Exponential Spatial Correlation with Large-Scale Fading Variations in Massive MIMO Channel Estimation

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