Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas (1107.3862v2)

Abstract: The main focus and contribution of this paper is a novel network-MIMO TDD architecture that achieves spectral efficiencies comparable with "Massive MIMO", with one order of magnitude fewer antennas per active user per cell. The proposed architecture is based on a family of network-MIMO schemes defined by small clusters of cooperating base stations, zero-forcing multiuser MIMO precoding with suitable inter-cluster interference constraints, uplink pilot signals reuse across cells, and frequency reuse. The key idea consists of partitioning the users population into geographically determined "bins", such that all users in the same bin are statistically equivalent, and use the optimal network-MIMO architecture in the family for each bin. A scheduler takes care of serving the different bins on the time-frequency slots, in order to maximize a desired network utility function that captures some desired notion of fairness. This results in a mixed-mode network-MIMO architecture, where different schemes, each of which is optimized for the served user bin, are multiplexed in time-frequency. In order to carry out the performance analysis and the optimization of the proposed architecture in a clean and computationally efficient way, we consider the large-system regime where the number of users, the number of antennas, and the channel coherence block length go to infinity with fixed ratios. The performance predicted by the large-system asymptotic analysis matches very well the finite-dimensional simulations. Overall, the system spectral efficiency obtained by the proposed architecture is similar to that achieved by "Massive MIMO", with a 10-fold reduction in the number of antennas at the base stations (roughly, from 500 to 50 antennas).

• The paper proposes a network-MIMO TDD architecture that partitions users into geographical bins, optimizing scheme parameters per bin to achieve high spectral efficiency.
• Numerical results show the proposed architecture achieves massive MIMO spectral efficiency with a 10-fold reduction in antennas, from approximately 500 to 50.
• Reducing the required number of antennas substantially lowers the cost and complexity of deploying massive MIMO systems, enhancing their practical feasibility.

Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas

In the paper titled "Achieving 'Massive MIMO' Spectral Efficiency with a Not-so-Large Number of Antennas," the authors propose a novel approach to optimize the spectral efficiency of massive MIMO systems by significantly reducing the number of antennas required at base stations. Massive MIMO, which leverages a large number of antennas at the base stations to serve multiple users simultaneously, is a critical technology for enhancing the capacity and spectral efficiency of future wireless networks.

Summary

Contribution

The paper introduces a network-MIMO TDD architecture that achieves spectral efficiencies comparable to "Massive MIMO" but with significantly fewer antennas. The authors focus on a system that partitions the user population into geographically determined "bins" and serves each bin using an optimal network-MIMO scheme specific to that bin. Key contributions include:

• Novel Architecture: Instead of requiring hundreds of antennas, the proposed approach utilizes a reduced antenna array by leveraging specific configurations suitable for varied user clusters.
• Network-MIMO Schemes: The paper discusses various schemes characterized by different parameters such as cluster size, frequency reuse, and pilot reuse patterns that facilitate interference management and enhance system spectral efficiency.
• Asymptotic Analysis: Using a large-system asymptotic analysis, the authors provide closed-form expressions for achievable rates, enabling efficient system optimization without the need for extensive simulations.
• Comparison with Traditional Approaches: The paper contrasts its proposed method with existing massive MIMO systems, demonstrating substantial improvements in spectral efficiency with fewer antennas.

Strong Numerical Results

The proposed network-MIMO architecture demonstrates robust spectral efficiencies comparable to traditional massive MIMO, with significant numerical findings including:

• 10-fold Reduction in Antennas: Spectral efficiency similar to traditional massive MIMO is achieved with a 10-fold reduction in antennas from approximately 500 to 50 per base station.
• Location-Specific Optimization: By systematically optimizing network-MIMO schemes for each user bin based on their geographical location, the architecture provides tailored solutions that maximize throughput and efficiency.

Theoretical and Practical Implications

Theoretically, this approach challenges the traditional scaling assumptions of massive MIMO systems, demonstrating that high spectral efficiencies are attainable with manageable antenna arrays. Practically, reducing the number of antennas required substantially lowers the cost and complexity of deploying massive MIMO systems, making them more feasible for real-world application.

Future Work and Speculation

The authors suggest further research into optimizing the user partition strategies in the presence of varying shadowing conditions and user mobility. Additionally, investigating the interaction of this approach with other interference management and scheduling techniques in multi-cell networks could enhance its applicability.

By providing a mechanism to achieve desired spectral efficiencies with fewer antennas, this work offers a promising pathway for the deployment of future cellular networks, balancing cost and performance benefits.