Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks

Göttsch, Fabian; Osawa, Noboru; Ohseki, Takeo; Yamazaki, Kosuke; Caire, Giuseppe

doi:10.1109/twc.2022.3223284

Cited by 7 publications

(29 citation statements)

References 26 publications

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“…Using the dynamic scheduling framework of [14], hard and proportional fairness scheduling (resp., HFS and PFS) are addressed. A system design challenge with a high UE density consists of the assignment of uplink (UL) pilots for channel estimation and the user-centric cluster formation [4], [7]. This problem is exacerbated in the presence of dynamic scheduling, since the set of active user changes at every scheduling decision (time slot).…”

Section: A Related Literaturementioning

confidence: 99%

“…We consider partial channel state information obtained by subspace projection channel estimation. Each RU computes locally the channel estimates p h ,k pt, f q for UEs k P U ptq from the received orthogonal UL pilot signal, where perfect subspace knowledge is assumed (see [7] for details).…”

Section: A Uplink Decoding With Partial Channel State Informationmentioning

confidence: 99%

“…Since, as said before, the statistics of I k pv k ptq, Hptqq for a UE k are generally extremely hard to obtain and depend on the scheduling policy itself, here we consider the localized adaptive scheme proposed in [9], where each user k collects a sliding window of N past samples of the instantaneous mutual information and optimizes its transmission rate r k using the empirical complementary CDF based on these samples. 5 In the following, we let Rk " r k P k pr k q, i.e., the maximum of the objective function in the right-hand side of (7).…”

Section: A Rate Allocationmentioning

confidence: 99%

“…2] leading to overall large UE data rates, recent works considered the more realistic UE density regime K ą L, where K is comparable to M L (i.e., in the same order of magnitude) taking into account multi-antenna RUs. This regime yields a relatively unfair distribution of the UE data rates [6], [7]. 1 The set of integers from 1 to N is denoted by rN s.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, the scheduler must be designed to achieve some desired form of fairness of the per-user throughput distribution. Finally, also as a consequence of this setting, we notice that the familiar ergodic rate used as performance metric in most standard literature on cell-free networks (e.g., see [4]- [7]) is not relevant any longer. In fact, the scheduler must allocate an "instantaneous" rate on each RB (or block of F RBs) and decoding is performed block by block, such that averaging over a virtually infinite sequence of fading states is no longer possible.…”

Section: Introductionmentioning

confidence: 99%

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Fairness Scheduling in Dense User-Centric Cell-Free Massive MIMO Networks

Göttsch

Osawa

Ohseki

et al. 2022

2022 56th Asilomar Conference on Signals, Systems, and Computers

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We consider fairness scheduling in a user-centric cell-free massive MIMO network, where L remote radio units, each with M antennas, serve K « LM user equipments (UEs). Recent results show that the maximum network sum throughput is achieved where Kact « LM 2 UEs are simultaneously active in any given time-frequency slots. However, the number of users K in the network is usually much larger. This requires that users are scheduled over the time-frequency resource and achieve a certain throughput rate as an average over the slots. We impose throughput fairness among UEs with a scheduling approach aiming to maximize a concave component-wise non-decreasing network utility function of the per-user throughput rates. In cell-free user-centric networks, the pilot and cluster assignment is usually done for a given set of active users. Combined with fairness scheduling, this requires pilot and cluster reassignment at each scheduling slot, involving an enormous overhead of control signaling exchange between network entities. We propose a fixed pilot and cluster assignment scheme (independent of the scheduling decisions), which outperforms the baseline method in terms of UE throughput, while requiring much less control information exchange between network entities.

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Section: A Related Literaturementioning

confidence: 99%

Section: A Uplink Decoding With Partial Channel State Informationmentioning

confidence: 99%

Section: A Rate Allocationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fairness Scheduling in Dense User-Centric Cell-Free Massive MIMO Networks

Göttsch

Osawa

Ohseki

et al. 2022

2022 56th Asilomar Conference on Signals, Systems, and Computers

Self Cite

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Joint optimal beamforming and power control in cell-free massive MIMO

Miretti

Cavalcante

Stańczak

2022

GLOBECOM 2022 - 2022 IEEE Global Communications Conference

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This study presents novel applications of fixed-point methods to solve previously open joint power control and beamforming design problems in modern large-scale MIMO systems, e.g., based on the cell-free massive MIMO and XL-MIMO concepts. In particular, motivated by the need for scalable system architectures, we revisit the classical sum power minimization and max-min fair design criteria by considering long-term power control and beamforming design based on channel statistics and possibly limited channel state information (CSI) sharing across distributed processing units. This approach is believed to mitigate the severe scalability issues of competing short-term optimal algorithms in the literature, which must be executed for every channel realization by a central controller endowed with global CSI, hence imposing very demanding requirements in terms of computation and interconnection capabilities. The obtained optimal algorithms are then illustrated and compared against existing short-term and long-term approaches via numerical simulations in a cell-free massive MIMO setup.

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Unlocking the Potential of Local CSI in Cell-Free Networks with Channel Aging and Fronthaul Delays

Miretti,

Stańczak

2024

ICC 2024 - IEEE International Conference on Communications

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Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks

Cited by 7 publications

References 26 publications

Fairness Scheduling in Dense User-Centric Cell-Free Massive MIMO Networks

Fairness Scheduling in Dense User-Centric Cell-Free Massive MIMO Networks

Joint optimal beamforming and power control in cell-free massive MIMO

Unlocking the Potential of Local CSI in Cell-Free Networks with Channel Aging and Fronthaul Delays

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