A scalable architecture for massive MIMO base stations using distributed processing

Abstract

Massive MIMO is an emerging technology for future wireless systems that has received much attention from both academia and industry recently. The most prominent feature of Massive MIMO is that the base station is equiped with a large number of antennas. It is therefore important to create scalable architectures to enable simple deployment in different configurations.In this thesis, a distributed architecture for performing the baseband processing in a massive OFDM MU-MIMO system is proposed and analyzed. The proposed architecture is based on connecting several identical nodes in a K-ary tree. It is shown that, depending on the chosen algorithms, all or most computations can be performed in a distrbuted manner. Also, the computational load of each node does not depend on the number of nodes in the tree (except for some timing issues) which implies simple scalability of the system.It is shown that it should be enough that each node contains one or two complex multipliers and a few complex adders running at a couple of hundres MHz to support specifications similar to LTE. Additionally the nodes must communicate with each other over links with data rates in the order of some Gbps.Finally, a VHDL implementation of the system is proposed. The implementation is parameterized such that a system can be generated from a given specification. Nyckelord KeywordsElektroteknik, ASIC, Massiv MIMO AbstractMassive MIMO is an emerging technology for future wireless systems that has received much attention from both academia and industry recently. The most prominent feature of Massive MIMO is that the base station is equiped with a large number of antennas. It is therefore important to create scalable architectures to enable simple deployment in different configurations.In this thesis, a distributed architecture for performing the baseband processing in a massive OFDM MU-MIMO system is proposed and analyzed. The proposed architecture is based on connecting several identical nodes in a K-ary tree. It is shown that, depending on the chosen algorithms, all or most computations can be performed in a distrbuted manner. Also, the computational load of each node does not depend on the number of nodes in the tree (except for some timing issues) which implies simple scalability of the system.It is shown that it should be enough that each node contains one or two complex multipliers and a few complex adders running at a couple of hundres MHz to support specifications similar to LTE. Additionally the nodes must communicate with each other over links with data rates in the order of some Gbps.Finally, a VHDL implementation of the system is proposed. The implementation is parameterized such that a system can be generated from a given specification.iii

Decentralized Equalization With Feedforward Architectures for Massive MU-MIMO

“…Feedforward architectures for decentralized massive MU-MIMO equalization have been proposed in [1], [7], [12], [21]. The present paper extends our theoretical results from [1] and, in contrast to [7], [12], [21], provides two distinct architectures and a corresponding SINR analysis for a range of linear and nonlinear equalization algorithms. In addition, we provide reference implementation results on a GPU cluster to assess the throughput and latency of our architectures and algorithms.…”

Modular Binary Tree Architecture for Distributed Large Intelligent Surface

“…There is a current trend toward decentralized architectures to address the problems associated to centralized processing in massive MIMO systems. In the available literature we find solutions ranging from fully decentralized [8][9][10][11], to partially decentralized architectures [12][13][14]. There are also attempts to face this problem in LIS such as [15][16][17], where approximate zero-forcing equalization is achieved through decentralized message passing between antennas within a LIS panel.…”

Decentralized Massive MIMO Processing Exploring Daisy-Chain Architecture and Recursive Algorithms

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