Performance of Distributed Massive MIMO and Small-Cell Systems Under Hardware and Channel Impairments

Elhoushy, Salah; Hamouda, Walaa

doi:10.1109/tvt.2020.2998405

Cited by 43 publications

(27 citation statements)

References 46 publications

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“…Uplink processing MMSE [59,124,145,146] ZF [147] Power allocation and load balancing [148] Max-min power control [149] Pilot power control [150] Sequential linear MMSE [120] mmWave Limited fronthaul capacity [151] Power control [152] Channel modeling [153] Energy efficiency [154] Energy Efficiency [116,132,[155][156][157] Imperfect Fronthaul [158][159][160][161][162][163][164] Low Resolution ADCs [163,[165][166][167] Hardware Impairments [164,[168][169][170] Non-orthogonal [171][172][173][174][175] Multiple Access…”

Section: Topics Aspects and Referencesmentioning

confidence: 99%

Cell-Free Massive MIMO : Scalability, Signal Processing and Power Control

Interdonato

2020

Linköping Studies in Science and Technology. Dissertations

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Linköping 2020 This is a Swedish Doctor of Philosophy thesis. The Doctor of Philosophy degree comprises 240 ECTS credits of postgraduate studies. Cover: Illustration of the Ericsson Radio Stripes concept, co-invented by the author of this thesis. The Radio Stripes constitute a way to implement a cell-free massive MIMO system. They aim at enabling invisible, low-cost deployment of large number of distributed access points in the vicinity of the users. This is achieved by serial integration of several transmitting and receiving components into a cable (or stripe) which also provides fronthaul communication and power supply.

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Section: Topics Aspects and Referencesmentioning

confidence: 99%

Cell-Free Massive MIMO : Scalability, Signal Processing and Power Control

Interdonato

2020

Linköping Studies in Science and Technology. Dissertations

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“…In this paper, the capacity of SCs to provide coverage in 5G/B5G wireless networks is explored under the umbrella of the IA paradigm. A fully distributed topology as in [20][21][22] is considered, where there are no macro base stations and a large number of APs act as small base stations to provide communication services to a much smaller number of MSs. The system is modeled as a downlink K-user interference channel network, where each MS receives data from a single AP [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…The system is modeled as a downlink K-user interference channel network, where each MS receives data from a single AP [6,7]. Moreover, each MS and its corresponding AP are considered an SC as in [20][21][22]. The transmission within an SC causes interference to the remaining users.…”

Section: Introductionmentioning

confidence: 99%

“…The transmission within an SC causes interference to the remaining users. We note that the network architecture is somewhat similar to that considered in the cell-free related literature (see [20][21][22]); however, the studied setup only requires for APs/MSs within a cluster to share their CSI whereas cell-free study requires the distribution of all users' data to all APs. Furthermore, we consider multiple antennas at the transmitter and receiver, thus enabling the incorporation of precoding/combining techniques at both sides to increase the achievable SE of the network.…”

Section: Introductionmentioning

confidence: 99%

“…Interference is only taken into account in the clustered-IA stage because considering the SINR to perform the AP/MS pair assignment and then to form the clusters would involve an iterative process with prohibitive complexity. Note that, in practical applications, the use of the SNR to decide the AP/MS pair is a common practice in the literature [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Deployment of Clustered‐Based Small Cells in Interference‐Limited Dense Scenarios: Analysis, Design, and Trade‐Offs

Villalonga

Riera-Palou

García

et al. 2021

Wireless Communications and Mobile Computing

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Network densification is one of the most promising solutions to address the high data rate demands in 5G and beyond (B5G) wireless networks while ensuring an overall adequate quality of service. In this scenario, most users experience significant interference levels from neighbouring mobile stations (MSs) and access points (APs) making the use of advanced interference management techniques mandatory. Clustered interference alignment (IA) has been widely proposed to manage the interference in densely deployed scenarios with a large number of users. Nonetheless, the setups considered in previous works are still far from the densification levels envisaged for 5G/B5G networks that are considered in this paper. Moreover, prior designs of clustered-IA systems relied on oversimplified channel models and/or enforced single-stream transmission. In this paper, we explore an ultradense deployment of small cells (SCs) to provide coverage in 5G/B5G wireless networks. A novel cluster design based on a size-restricted k -means algorithm to divide the SCs into different clusters is proposed taking into account path loss and shadowing effects, thus providing a more realistic solution than those available in the current literature. Unlike previous works, this clustering method can also cater for spatial multiplexing scenarios. Also, several design parameters such as the number of transmit antennas, multiplexed data streams, and deployed APs are analyzed in order to identify trade-offs between performance and complexity. The relationship between density of network elements per area unit and performance is investigated, thus allowing to illustrate that there is an optimal coverage area value over which the network resources should be distributed. Moreover, it is shown that the spectral-efficiency degradation due to the intercluster interference in ultradense networks (UDNs) points to the need of designing an interference management algorithm that accounts for both intracluster and intercluster interferences. Simulation results provide key insights for the deployment of small cells in interference-limited dense scenarios.

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A combinatorial precoding scheme of cell‐free massive MIMO with channel aging

Fang

Yang

et al. 2022

IET Communications

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Here, we investigate the precoding schemes for the downlink data transmission of a time‐division duplex cell‐free massive multiple‐input multiple‐output (MIMO) system with channel aging, which arises from the user mobility. Closed‐form spectral efficiency (SE) expressions of the downlink with the normalized conjugate beamforming (NCB), and the full‐pilot zero‐forcing (FZF), are derived, which are used for the analytical system performance evaluation. Then, a novel combinatorial precoding scheme with enhanced system SE performance, which adopts either NCB or FZF according to each user channel aging condition, is proposed. Moreover, a pilot allocation strategy is proposed to alleviate the extra interference brought by the combinatorial precoding scheme. Also, a statistical channel cooperative power control is employed to further improve the performance for all the above precoding schemes. Numerical results show that the proposed precoding scheme can substantially improve the average downlink SE.

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Performance of Distributed Massive MIMO and Small-Cell Systems Under Hardware and Channel Impairments

Cited by 43 publications

References 46 publications

Cell-Free Massive MIMO : Scalability, Signal Processing and Power Control

Cell-Free Massive MIMO : Scalability, Signal Processing and Power Control

Deployment of Clustered‐Based Small Cells in Interference‐Limited Dense Scenarios: Analysis, Design, and Trade‐Offs

A combinatorial precoding scheme of cell‐free massive MIMO with channel aging

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