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Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems With Multi-Antenna Users
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3599-5584
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-2298-6774
2013 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, no 13, 3431-3446 p.Article in journal (Refereed) Published
Abstract [en]

In downlink multi-antenna systems with many users, the multiplexing gain is strictly limited by the number of transmit antennas and the use of these antennas. Assuming that the total number of receive antennas at the multi-antenna users is much larger than, the maximal multiplexing gain can be achieved with many different transmission/reception strategies. For example, the excess number of receive antennas can be utilized to schedule users with effective channels that are near-orthogonal, for multi-stream multiplexing to users with well-conditioned channels, and/or to enable interference-aware receive combining. In this paper, we try to answer the question if the data streams should be divided among few users (many streams per user) or many users (few streams per user, enabling receive combining). Analytic results are derived to show how user selection, spatial correlation, heterogeneous user conditions, and imperfect channel acquisition (quantization or estimation errors) affect the performance when sending the maximal number of streams or one stream per scheduled user-the two extremes in data stream allocation. While contradicting observations on this topic have been reported in prior works, we show that selecting many users and allocating one stream per user (i.e., exploiting receive combining) is the best candidate under realistic conditions. This is explained by the provably stronger resilience towards spatial correlation and the larger benefit from multi-user diversity. This fundamental result has positive implications for the design of downlink systems as it reduces the hardware requirements at the user devices and simplifies the throughput optimization.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2013. Vol. 61, no 13, 3431-3446 p.
Keyword [en]
Block-diagonalization, channel estimation, limited feedback, multi-user MIMO, receive combining, zero-forcing
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-125858DOI: 10.1109/TSP.2013.2260331ISI: 000321151800014Scopus ID: 2-s2.0-84879121660OAI: oai:DiVA.org:kth-125858DiVA: diva2:641248
Funder
EU, European Research Council, 228044Swedish Research Council, 2012-228
Note

QC 20130816

Available from: 2013-08-16 Created: 2013-08-15 Last updated: 2017-12-06Bibliographically approved

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Bengtsson, MatsOttersten, Björn

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