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Decentralizing Coherent Joint Transmission Precoding via Fast ADMM with Deterministic Equivalents

Xinyu Bian, Yuhao Liu, Yizhou Xu, Tianqi Hou, Wenjie Wang, Yuyi Mao, Jun Zhang

TL;DR

This paper investigates advanced precoding techniques for coordinated multi-point (CoMP) with downlink coherent joint transmission with downlink coherent joint transmission, an effective approach for ICI suppression and proposes a decentralized scheme to minimize the total power consumption.

Abstract

Inter-cell interference (ICI) suppression is critical for multi-cell multi-user networks. In this paper, we investigate advanced precoding techniques for coordinated multi-point (CoMP) with downlink coherent joint transmission, an effective approach for ICI suppression. Different from the centralized precoding schemes that require frequent information exchange among the cooperating base stations, we propose a decentralized scheme to minimize the total power consumption. In particular, based on the covariance matrices of global channel state information, we estimate the ICI bounds via the deterministic equivalents and decouple the original design problem into sub-problems, each of which can be solved in a decentralized manner. To solve the sub-problems at each base station, we develop a low-complexity solver based on the alternating direction method of multipliers (ADMM) in conjunction with the convex-concave procedure (CCCP). Simulation results demonstrate the effectiveness of our proposed decentralized precoding scheme, which achieves performance similar to the optimal centralized precoding scheme. Besides, our proposed ADMM solver can substantially reduce the computational complexity, while maintaining outstanding performance.

Decentralizing Coherent Joint Transmission Precoding via Fast ADMM with Deterministic Equivalents

TL;DR

This paper investigates advanced precoding techniques for coordinated multi-point (CoMP) with downlink coherent joint transmission with downlink coherent joint transmission, an effective approach for ICI suppression and proposes a decentralized scheme to minimize the total power consumption.

Abstract

Inter-cell interference (ICI) suppression is critical for multi-cell multi-user networks. In this paper, we investigate advanced precoding techniques for coordinated multi-point (CoMP) with downlink coherent joint transmission, an effective approach for ICI suppression. Different from the centralized precoding schemes that require frequent information exchange among the cooperating base stations, we propose a decentralized scheme to minimize the total power consumption. In particular, based on the covariance matrices of global channel state information, we estimate the ICI bounds via the deterministic equivalents and decouple the original design problem into sub-problems, each of which can be solved in a decentralized manner. To solve the sub-problems at each base station, we develop a low-complexity solver based on the alternating direction method of multipliers (ADMM) in conjunction with the convex-concave procedure (CCCP). Simulation results demonstrate the effectiveness of our proposed decentralized precoding scheme, which achieves performance similar to the optimal centralized precoding scheme. Besides, our proposed ADMM solver can substantially reduce the computational complexity, while maintaining outstanding performance.
Paper Structure (21 sections, 2 theorems, 61 equations, 6 figures, 1 table, 2 algorithms)

This paper contains 21 sections, 2 theorems, 61 equations, 6 figures, 1 table, 2 algorithms.

Key Result

Theorem 1

Let Assumptions eq:ass2 and eq:ass3 hold. We have $\max_{i,p} |\lambda_{ip}^* - \bar{\lambda}_{ip}| \to 0$ almost surely where and $\bar{m}_{ip}$ is given by the unique non-negative solution to the following system equations:

Figures (6)

  • Figure 1: A downlink CJT system, where the cell-edge UEs are served by multiple coordinating BSs simutaneously.
  • Figure 2: The IP-RAN architecture for the proposed decentralized CJT precoding scheme.
  • Figure 3: Total power consumption versus the number of antennas at each BS.
  • Figure 4: Sum rate versus the number of antennas at each BS.
  • Figure 5: Sum rate versus the scale factor of the interference bounds.
  • ...and 1 more figures

Theorems & Definitions (5)

  • Theorem 1
  • proof
  • Theorem 2
  • proof
  • Remark 1