Graduate School and Research Center in Digital Sciences

Enabling covariance-based feedback in massive MIMO: A user classification approach

Qiu, Shuang; Gesbert, David; Jiang, Tao

ASILOMAR 2018, 52nd Asilomar Conference on Signals, Systems and Computers, 28-31 October 2018, Pacific Grove, USA

In this paper, we propose a novel channel feedback scheme for frequency division duplexing massive multi-input multi-output systems. The concept uses the notion of user statistical separability which was hinted in several prior works in the massive antenna regime but not fully exploited so far. We here propose a hybrid statistical-instantaneous feedback scheme based on a user classification mechanism where the classification metric derives from a rate bound analysis. According to classification results, a user either operates on a statistical feedback mode or instantaneous mode. Our results illustrate the sum rate advantages of our scheme under a global feedback overhead constraint. 

Document Doi Arxiv Bibtex

Title:Enabling covariance-based feedback in massive MIMO: A user classification approach
City:Pacific Grove
Department:Communication systems
Eurecom ref:5614
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Bibtex: @inproceedings{EURECOM+5614, doi = {}, year = {2018}, title = {{E}nabling covariance-based feedback in massive {MIMO}: {A} user classification approach}, author = {{Q}iu, {S}huang and {G}esbert, {D}avid and {J}iang, {T}ao}, booktitle = {{ASILOMAR} 2018, 52nd {A}silomar {C}onference on {S}ignals, {S}ystems and {C}omputers, 28-31 {O}ctober 2018, {P}acific {G}rove, {USA} }, address = {{P}acific {G}rove, {UNITED} {STATES}}, month = {10}, url = {} }
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