Distributed Massive MIMO: A Diversity Combining Method for TDD Reciprocity Calibration

Chen, Cheng-Ming; Blandino, Steve; Gaber, Abdo; Desset, Claude; Bourdoux, André; Perre, Liesbet Van der; Pollin, Sofie

doi:10.1109/glocom.2017.8254817

Cited by 27 publications

(19 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, compared with the case where the downlink transmit SNR ρ t = 10 dB, the higher SNR case requires lower calibration SNR to achieve the same system performance, which implies that both the downlink transmit SNR and the calibration SNR contribute to the improvement of the system performance. This result is consistent to the theoretical analysis in (29). Also, the proposed two-stage calibration needs lower SNR to achieve the same performance, especially at the lower SNR regime.…”

Section: B Calibration Performancesupporting

confidence: 90%

“…used cell-edge UEs to support the calibration [28], and C. Chen at el. exploited maximum ratio combining and maximum ratio transmitting methods to combine calibration signals [29]. For reducing the overhead of the CSI feedback among BSs, a decentralized calibration was presented based on decoupling the whole calibration problem into several BS-level subproblems in [30].…”

Section: Introductionmentioning

confidence: 99%

“…(sinc(θ t )sinc(θ r )) −2 . From(29), the calibration gain increases when the SNRs of both the transmit signals and the calibration signals increase. Hence, if ρ c , ρ 1 and ρ 2 are large enough, the calibration gain G c > 0.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Relaying Systems With Reciprocity Mismatch: Impact Analysis and Calibration

Nie

Chen

Zhao

et al. 2020

IEEE Trans. Commun.

View full text Add to dashboard Cite

show abstract

Section: B Calibration Performancesupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Relaying Systems With Reciprocity Mismatch: Impact Analysis and Calibration

Nie

Chen

Zhao

et al. 2020

IEEE Trans. Commun.

View full text Add to dashboard Cite

show abstract

“…For K iterations for capacity based scheduling massive MIMO research [4,31]. The main components of our testbed and their functionalities are described in Table III.…”

Section: 4e3mentioning

confidence: 99%

“…Note that for a distributed massive MIMO system, other design perspectives have to be considered. For instance, the TDD reciprocity calibration algorithm of a distributed massive MIMO has been improved in [31]; it reduces the downlink precoded inter-user interference.…”

Section: 4e3mentioning

confidence: 99%

User Scheduling and Antenna Topology in Dense Massive MIMO Networks: An Experimental Study

Chen

Wang

Gaber³

et al. 2020

IEEE Trans. Wireless Commun.

Self Cite

View full text Add to dashboard Cite

A massive MIMO network can serve ten's of users simultaneously. However, in dense scenarios the users are potentially closely-spaced, potentially resulting in substantial inter-user interference. Scheduling can overcome this by selecting the users that lead to the highest combined spectral efficiency. As scheduling comes with a significant pilot overhead, an alternative strategy could minimize user correlation by distributing the antenna elements in space. In this paper, we propose a comprehensive system study including antenna topology and distribution, user scheduling and pilot overhead reduction. Our user scheduling and pilot reduction algorithms are evaluated using system level simulations relying on indoor line-of-sight channel measurements from a 64 antenna base station at 2.61GHz. To have a thorough evaluation of the proposed algorithm, we consider four different antenna topologies, including co-located and distributed placement of the base station arrays. Our evaluation shows that in a conference room with 64 densely deployed users, our proposed low complexity algorithm can improve the spectral efficiency by at least 14% compared to random user selection with the best antenna distribution strategy. Finally, our results show that by relying on channel hardening, we reduce the pilot overhead by 3.2x.

show abstract