Full-Duplex Cell-Free Massive MIMO

Vu, Tung T.; Ngo, Duy T.; Ngo, Hien Quoc; Le‐Ngoc, Tho

doi:10.1109/icc.2019.8761711

Cited by 49 publications

(113 citation statements)

References 13 publications

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“…1 We model these channels as g d mk = (β d mk ) 1/2gd mk and g u ml = (β u ml ) 1/2gu ml . Here β d mk and β u ml ∈ R are corresponding large scale fading coefficients, which are same for all antennas at the mth AP [5], [21]. The vectorsg d mk andg u ml denote small scale fading with independent and identically distributed (i.i.d.)…”

Section: )mentioning

confidence: 99%

“…CN (0, 1) entries. The UDI channel between the kth downlink UE and lth uplink UE is modeled as h kl = (β kl ) 1/2h kl [5], [6], whereβ kl is the large scale fading coefficient andh kl ∼ CN (0, 1) is the small scale fading. The inter-and intra-AP channels from the transmit antennas of the ith AP to the receive antennas of the mth AP are denoted as H mi ∈ C Nr×Nt for i = 1 to M .…”

Section: )mentioning

confidence: 99%

“…Full-duplex (FD) wireless systems have now been practically realized with advanced selfinterference (SI) cancellation mechanisms [4]. FD CF mMIMO is a relatively recent area of interest [5]- [7], where access points (APs) simultaneously serve downlink and uplink user equipments (UEs) on the same spectral resource. Vu et al in [5] considered a FD CF mMIMO system with maximum-ratio combining and showed that if SI at the APs is suppressed up to a certain limit, it has higher throughput than its half-duplex (HD) counterpart and FD co-located systems.…”

Section: Introductionmentioning

confidence: 99%

“…The existing FD CF mMIMO literature assumes high-capacity fronthaul links [5]- [7]. These links, however, have limited capacity, and the information needs to be consequently quantized and sent over them.…”

Section: Introductionmentioning

confidence: 99%

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Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization

Datta¹,

Sharma²,

Amudala³

et al. 2021

Preprint

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<p>Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of full-duplex (FD) communications, we consider a FD CF mMIMO system with practical limited-capacity fronthaul links. We derive closed-form spectral efficiency (SE) lower bounds for this system with maximum-ratio combining/maximum-ratio transmission processing and optimal uniform quantization. We then optimize the weighted sum EE (WSEE) via downlink and uplink power control by using a two-layered approach: the first layer formulates the optimization as a generalized convex program, while the second layer solves the optimization decentrally using alternating direction method of multipliers. We analytically show that the proposed two-layered formulation yields a Karush-Kuhn-Tucker point of the original WSEE optimization. We numerically show the influence of weights on the individual EE of the users, which demonstrates the utility of WSEE metric to incorporate heterogeneous EE requirements of users. We show that the low fronthaul capacity reduces the number of users each AP can support, and the cell-free system, consequently, becomes user-centric.</p>

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Section: )mentioning

confidence: 99%

Section: )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization

Datta¹,

Sharma²,

Amudala³

et al. 2021

Preprint

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“…Deep Learning [176][177][178][179][180] Channel Model Rician fading [181][182][183] Spatially correlated Rayleigh fading [184][185][186] Miscellaneous Full-duplex [187][188][189] Channel non-reciprocity [190] Asynchronous reception [191] System information broadcast [192] Over-the-air signaling [193,194] Multi-antenna users [195,196] Frequency division duplex [197] Stochastic geometry [198] Dynamic Resource allocation [199] Wireless power transfer [200]…”

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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On proportional fairness of uplink spectral efficiency in cell‐free massive MIMO systems

Pham

Kha

Khanh

2020

Int J Communication

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This paper is concerned with the proportional fairness (PF) of the spectral efficiency (SE) maximization of uplinks in a cell-free (CF) massive multiple-input multiple-output (MIMO) system in which a large number of single-antenna access points (APs) connected to a central processing unit (CPU) serve many single-antenna users. To detect the user signals, the APs use matched filters based on the local channel state information while the CPU deploys receiver filters based on knowledge of channel statistics. We devise the maximization

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Full-Duplex Cell-Free Massive MIMO

Cited by 49 publications

References 13 publications

Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization

Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization

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

On proportional fairness of uplink spectral efficiency in cell‐free massive MIMO systems

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