Decentralized Massive MIMO Processing Exploring Daisy-Chain Architecture and Recursive Algorithms
TL;DR: In this article, a decentralized algorithm for uplink detection and downlink precoding based on the Coordinate Descent (CD) method is proposed, which does not require a central node for these tasks.
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Abstract: Algorithms for Massive MIMO uplink detection and downlink precoding typically rely on a centralized approach, by which baseband data from all antenna modules are routed to a central node in order to be processed. In the case of Massive MIMO, where hundreds or thousands of antennas are expected in the base-station, said routing becomes a bottleneck since interconnection throughput is limited. This paper presents a fully decentralized architecture and an algorithm for Massive MIMO uplink detection and downlink precoding based on the Coordinate Descent (CD) method, which does not require a central node for these tasks. Through a recursive approach and very low complexity operations, the proposed algorithm provides a good trade-off between performance, interconnection throughput and latency. Further, our proposed solution achieves significantly lower interconnection data-rate than other architectures, enabling future scalability.
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Citations
MMSE-Optimal Sequential Processing for Cell-Free Massive MIMO With Radio Stripes
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Team MMSE Precoding with Applications to Cell-free Massive MIMO.
TL;DR: In this paper, a novel distributed precoding design, coined team minimum mean-square error (TMMSE) precoding, which rigorously generalizes classical centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSIT), is proposed.
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Full-Duplex Cell-Free Massive MIMO Systems: Analysis and Decentralized Optimization
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References
Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas
TL;DR: A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval and a complete multi-cellular analysis yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve.
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Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays
Fredrik Rusek,Daniel Persson,Buon Kiong Lau,Erik G. Larsson,Thomas L. Marzetta,Fredrik Tufvesson +5 more
TL;DR: The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time.
Scaling up MIMO: Opportunities and Challenges with Very Large Arrays
Fredrik Rusek,Daniel Persson,Buon Kiong Lau,Erik G. Larsson,Thomas L. Marzetta,Ove Edfors,Fredrik Tufvesson +6 more
TL;DR: Very large MIMO as mentioned in this paper is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation.
Cell-Free Massive MIMO Versus Small Cells
TL;DR: In this paper, the authors proposed a max-min power control algorithm to ensure uniformly good service throughout the area of coverage in a cell-free massive MIMO system, where each user is served by a dedicated access point.
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Cell-Free Massive MIMO versus Small Cells
TL;DR: Under uncorrelated shadow fading conditions, the cell-free scheme provides nearly fivefold improvement in 95%-likely per-user throughput over the small-cell scheme, and tenfold improvement when shadow fading is correlated.