Optimal Massive-MIMO-Aided Clustered Base-Station Coordination

Li, Xueru; Zhang, Xu; Zhou, Yongxing; Hanzo, Lajos

doi:10.1109/tvt.2021.3056875

Cited by 15 publications

(13 citation statements)

References 26 publications

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“…Note that the large-scale fading coefficient is modeled by path-loss only in (3) while the shadowing is ignored. To see whether the optimal AP-selection ratio λ * that maximizes the average energy efficiency remains the same when shadowing is taken into consideration, let us model the large-scale fading coefficient γ k,l from AP b l to user u k with shadowing as UCR-ApSel with * given in (34) Graph partitioning algorithm in [15] AP-centric clustering algorithm in [21] User-centric clustering algorithm in [24] 4.0 4.5 5.0 0.50 0.55 where c k,l ∼ N (0, σ 2 sh ) is a normal random variable with zero mean and standard deviation σ sh . In the case of no shadowing, i.e., σ sh = 0, (36) reduces to (3) in the paper, where the large-scale fading coefficient is solely determined by the path-loss.…”

Section: Discussionmentioning

confidence: 99%

Average Downlink Rate Analysis for Clustered Cell-Free Networks with Access Point Selection

Ouyang

Wang

Liu

2022

2022 IEEE International Symposium on Information Theory (ISIT)

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Ultra-densely deploying access points (APs) to support the increasing data traffic would significantly escalate the cell-edge problem resulting from traditional cellular networks. By removing the cell boundaries and coordinating all APs for joint transmission, the cell-edge problem can be alleviated, which in turn leads to unaffordable system complexity and channel measurement overhead. A new scalable clustered cell-free network architecture has been proposed recently, under which the large-scale network is flexibly partitioned into a set of independent subnetworks operating parallelly. In this paper, we study the energy-efficient clustered cell-free networking problem with AP selection. Specifically, we propose a user-centric ratio-fixed AP-selection based clustering (UCR-ApSel) algorithm to form subnetworks dynamically. Following this, we analyze the average energy efficiency achieved with the proposed UCR-ApSel scheme theoretically and derive an effective closed-form upper-bound. Based on the analytical upper-bound expression, the optimal AP-selection ratio that maximizes the average energy efficiency is further derived as a simple explicit function of the total number of APs and the number of subnetworks. Simulation results demonstrate the effectiveness of the derived optimal AP-selection ratio and show that the proposed UCR-ApSel algorithm with the optimal AP-selection ratio achieves around 40% higher energy efficiency than the baselines. The analysis provides important insights to the design and optimization of future ultra-dense wireless communication systems.INDEX TERMS Clustered cell-free networking, subnetwork, clustering, energy efficiency analysis, access point selection I. IntroductionTraditional cellular network partitions the wireless network into a set of cells, and one base-station (BS) is located at the cell center to serve users within its coverage. Since users are randomly distributed, there might be users located in the cell boundary areas, leading to the well-known celledge problem, that is, the cell-edge users experience poor network services due to low received signal power and strong inter-cell interference. To support the extremely high data rate and low traffic delay of numerous intelligent devices and services, such as autonomous vehicles, smart homes, digital twins and holographic communications, BSs would be ultra-densely deployed in the sixth-generation (6G) mobile communication systems [2], which in turn exacerbates the cell-edge problem. Therefore, the cellular network architecture might not be suitable for future ultra-dense wireless communication systems.To avoid the cell-edge problem, coordinating all the geographically distributed access points (APs), which are equivalent to BSs, to jointly serve all users on the same

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Section: Discussionmentioning

confidence: 99%

Average Downlink Rate Analysis for Clustered Cell-Free Networks with Access Point Selection

Ouyang

Wang

Liu

2022

2022 IEEE International Symposium on Information Theory (ISIT)

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“…BS cooperation is being considered for 5G and beyond 5G (B5G) for efficient coverage and high throughput. For B5G, cell-free system is being proposed where a group of base stations cooperatively serve the users without creating autonomous cells while intelligently identifying the user's communication environments [11][12][13][14]. Base station cooperation technologies are also critical for providing reliable cell-edge service in the millimeter wave bands, even for high mobility scenarios.…”

Section: Cooperative Small Cellsmentioning

confidence: 99%

“…As described earlier, CoMP is a form of SBS cooperation, and it is being actively explored for implementation in 5G/B5G systems. Li et al [12] analyze coordinated beamforming/scheduling scheme for massive MIMO small-cell network and their analysis shows 2-4.5 times higher average sum-rate compared to non-cooperative massive MIMO network. This signifies SBS cooperation for future systems that are likely to have massive MIMO-based SBS.…”

Section: Cooperative Small Cellsmentioning

confidence: 99%

A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

et al. 2021

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Small cells deliver cost-effective capacity and coverage enhancement in a cellular network. In this work, we present the interplay of two technologies, namely Wi-Fi offloading and small-cell cooperation that help in achieving this goal. Both these technologies are also being considered for 5G and B5G (Beyond 5G). We simultaneously consider Wi-Fi offloading and small-cell cooperation to maximize average user throughput in the small-cell network. We propose two heuristic methods, namely Sequential Cooperative Rate Enhancement (SCRE) and Sequential Offloading Rate Enhancement (SORE) to demonstrate cooperation and Wi-Fi offloading, respectively. SCRE is based on cooperative communication in which a user data rate requirement is satisfied through association with multiple small-cell base stations (SBSs). However, SORE is based on Wi-Fi offloading, in which users are offloaded to the nearest Wi-Fi Access Point and use its leftover capacity when they are unable to satisfy their rate constraint from a single SBS. Moreover, we propose an algorithm to switch between the two schemes (cooperation and Wi-Fi offloading) to ensure maximum average user throughput in the network. This is called the Switching between Cooperation and Offloading (SCO) algorithm and it switches depending upon the network conditions. We analyze these algorithms under varying requirements of rate threshold, number of resource blocks and user density in the network. The results indicate that SCRE is more beneficial for a sparse network where it also delivers relatively higher average data rates to cell-edge users. On the other hand, SORE is more advantageous in a dense network provided sufficient leftover Wi-Fi capacity is available and more users are present in the Wi-Fi coverage area.

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“…In order to obtain spatial multiplexing gain, XL-MIMO should generate a directional beam with high array gain by beamforming. Before realizing beamforming, the channel state information (CSI) should be acquired in advance by channel estimation [6], [7]. Moreover, precise description of the transmission electromagnetic (EM) environment, or the channel model, is important for designing advanced channel estimation scheme.…”

Section: Introductionmentioning

confidence: 99%

Double-Side Near-Field Channel Estimation for Extremely Large-Scale MIMO System

Lu¹,

Dai²

2022

Preprint

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Accurate channel estimation is essential to empower extremely large-scale MIMO (XL-MIMO) in 6G networks with ultra-high spectral efficiency. Unfortunately, most of the existing channel estimation methods designed for XL-MIMO fail to consider a double-side near-field scenario, where both transmitter and receiver are equipped with extremely large-scale antenna arrays. The existing channel estimation schemes cannot be directly applied to the double-side near-field scenario. In this paper, based on this scenario, we first derive double-side near-field Rayleigh distance (DS-RD) and effective doubleside near-field Rayleigh distance (EDS-RD) to determine the range of the double-side near-field region.Then, a double-side near-field channel model is proposed to match this scenario, where the distance of the transmitter from the receiver is smaller than EDS-RD. In the proposed channel model, the line of sight (LoS) path component is modeled by the geometric free assumption while non-line of sight (NLoS) path components are modeled by the near-field array response vectors. Finally, a double-side near-field channel estimation algorithm is proposed to solve the channel estimation problem in this scenario, where the LoS path component and NLoS path components are estimated separately. Numerical simulation results demonstrate that, the proposed channel estimation algorithm is able to outperform the existing methods.

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Optimal Massive-MIMO-Aided Clustered Base-Station Coordination

Cited by 15 publications

References 26 publications

Average Downlink Rate Analysis for Clustered Cell-Free Networks with Access Point Selection

Average Downlink Rate Analysis for Clustered Cell-Free Networks with Access Point Selection

A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

Double-Side Near-Field Channel Estimation for Extremely Large-Scale MIMO System

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