Precoding Vector Computation in Distributed Massive MIMO Networks
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Solution Overview
Problem
Distributed Massive Multiple Input Multiple Output (MIMO) systems face challenges in efficient broadcast and multicast transmission due to limitations in channel state information acquisition and interference management, particularly in large-scale deployments where antenna distribution and path losses affect system performance.
Innovation Solution
The method involves obtaining long-term Channel State Information (CSI) at each Access Point, communicating it to a central processing system, computing a precoding vector based on this CSI, and broadcasting or multicasting data using this vector to improve reliability and efficiency in distributed cell-free MIMO networks, suitable for both micro and millimeter-wave frequencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed Massive MIMO systems use conventional multi-user MIMO techniques, then the system can support equal numbers of service antennas and terminals, but the system does not achieve scalable performance improvement and energy efficiency
Solution Approach 1:
The patent segments the base station antennas into multiple distributed access points (APs) geographically separated from each other. Each AP serves multiple terminals independently, allowing the system to scale by adding more distributed APs rather than concentrating all antennas at a single location. This segmentation enables the system to achieve throughput improvements while maintaining manageable complexity at each individual AP.
Solution Approach 2:
The patent transitions from a centralized two-dimensional antenna array to a three-dimensional distributed architecture where access points are spread across different geographical locations. This spatial distribution adds a new dimension to the MIMO system, enabling improved coverage and throughput without proportionally increasing the complexity of any single node.
2Reliability
If distributed Massive MIMO systems are deployed with geographically spread access points, then coverage and energy efficiency improve, but channel state information acquisition becomes more difficult due to path losses and interference
Solution Approach 1:
The patent combines channel state information from multiple distributed access points at a central processing unit. By merging the CSI measurements from multiple APs, the system overcomes the individual limitations of each distributed AP and achieves reliable channel knowledge across the entire service area, enabling improved coverage without sacrificing measurement accuracy.
Solution Approach 2:
The patent introduces a central processing unit as an intermediary that collects, processes, and manages channel state information from multiple distributed access points. This intermediary coordinates the CSI acquisition process, handles the path loss compensation, and manages the interference mitigation strategies, making the complex distributed CSI acquisition manageable and reliable.
3Reliability
If orthogonal pilot sequences are assigned to every terminal, then pilot contamination is eliminated, but the maximum number of supported terminals is limited by the coherence interval size
Solution Approach 1:
The patent assigns different pilot sequences locally at each access point based on the specific terminal distribution and channel conditions in that local area. Rather than using a single global orthogonal pilot set, each AP can independently manage its pilot assignments, allowing terminals in different geographical locations to reuse pilots without causing contamination, thus supporting more terminals while maintaining reliable interference management.
Solution Approach 2:
The patent implements dynamic pilot sequence assignment where the pilot configuration can change over time based on channel conditions, terminal mobility, and network load. This dynamic approach allows the system to adapt pilot reuse patterns to current conditions, enabling support for a larger number of terminals compared to static orthogonal pilot assignments while maintaining effective interference management through real-time adjustments.
Data Source
AI summary
Systems and methods for broadcast/multicast transmission in a distributed cell-free massive Multiple Input Multiple Output (MIMO) network are disclosed. In one embodiment, a method for broadcasting/multicasting data to User Equipments (UEs) comprises, at each Access Point (AP) of two or more APs, obtaining long-term Channel State Information (CSI) for a UE(s) and communicating the long-term CSI for the UE to a central processing system. The method further comprises, at the central processing system, receiving the long-term CSI for the UE from each AP, computing a precoding vector (w) for the UE(s) across the APs based on the long-term CSI, and communicating the precoding vector (w) to the APs. The method further comprises, at each AP, obtaining the precoding vector (w) from the central processing system, precoding data to be broadcast/multicast to the UE(s) based on the precoding vector (w), and broadcasting/multicasting the precoded data to the UE(s).