Linear Precoding in Cooperative MIMO Cellular Networks with Limited Coordination Clusters

Abstract

In a cooperative multiple-antenna downlink cellular network, maximization of a concave function of user rates is considered. A new linear precoding technique called soft interference nulling (SIN) is proposed, which performs at least as well as zero-forcing (ZF) beamforming. All base stations share channel state information, but each user's message is only routed to those that participate in the user's coordination cluster. SIN precoding is particularly useful when clusters of limited sizes overlap in the network, in which case traditional techniques such as dirty paper coding or ZF do not directly apply. The SIN precoder is computed by solving a sequence of convex optimization problems. SIN under partial network coordination can outperform ZF under full network coordination at moderate SNRs. Under overlapping coordination clusters, SIN precoding achieves considerably higher throughput compared to myopic ZF, especially when the clusters are large.

13 pages, 5 figures

Cited by in corpus (31)

• Joint Precoding and Multivariate Backhaul Compression for the Downlink of Cloud Radio Access Networks
• On the Spectral Efficiency of Full-Duplex Small Cell Wireless Systems
• Fast Converging Algorithm for Weighted Sum Rate Maximization in Multicell MISO Downlink
• CoMP Meets Smart Grid: A New Communication and Energy Cooperation Paradigm
• Rethinking WMMSE: Can Its Complexity Scale Linearly With the Number of BS Antennas?
• Fronthaul Compression and Transmit Beamforming Optimization for Multi-Antenna Uplink C-RAN
• Interference Coordination: Random Clustering and Adaptive Limited Feedback
• Distributed Fronthaul Compression and Joint Signal Recovery in Cloud-RAN
• Linear Precoding and Equalization for Network MIMO with Partial Cooperation
• Distributed Multicell Beamforming Design Approaching Pareto Boundary with Max-Min Fairness
• Cooperative Base Station Coloring for Pair-wise Multi-Cell Coordination
• A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data
• A Learning Aided Flexible Gradient Descent Approach to MISO Beamforming
• Meta-learning Based Beamforming Design for MISO Downlink
• Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogenous Networks
• Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks
• Deep unfolding of the weighted MMSE beamforming algorithm
• Asynchronous Distributed Coordinated Hybrid Precoding in Multi-cell mmWave Wireless Networks
• An efficient algorithm for weighted sum-rate maximization in multicell downlink beamforming
• Coordinated Linear Precoding in Downlink Multicell MU-MISO OFDMA Networks
• The Weighted Sum Rate Maximization in MIMO Interference Networks: The Minimax Lagrangian Duality and Algorithm
• Sparse Beamforming and User-Centric Clustering for Downlink Cloud Radio Access Network
• A low-latency control plane for dense cellular networks
• Content-Aware User Association and Multi-User MIMO Beamforming over Mobile Edge Caching
• Layered Group Sparse Beamforming for Cache-Enabled Green Wireless Networks
• Stochastic Modeling and Analysis of User-Centric Network MIMO Systems
• Improved Linear Precoding over Block Diagonalization in Multi-cell Cooperative Networks
• Two-Scale Stochastic Control for Multipoint Communication Systems with Renewables
• Low-Complexity Algorithm for Worst-Case Utility Maximization in Multiuser MISO Downlink
• Joint User Grouping and Linear Virtual Beamforming: Complexity, Algorithms and Approximation Bounds
• Convex Approximated Weighted Sum-Rate Maximization for Multicell Multiuser OFDM