Distributed DIDO Wireless Communication Interference Nulling
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Solution Overview
Problem
Current wireless communication technologies face challenges in high-density deployments due to co-channel interference and bandwidth limitations, particularly with Multi-User Multi-Input Multiple-Output (MU-MIMO) and Distributed-Input Distributed-Output (DIDO) techniques, which suffer from imperfect nulling, high network bandwidth requirements, and latency issues in centralized processing solutions.
Innovation Solution
A distributed processing DIDO system where multiple access points (APs) locally generate steering matrix information for spatial precoding and transmit waveforms, allowing coordinated simultaneous transmissions to multiple clients while nulling interference, using decentralized baseband signal processing and lightweight MAC coordination to optimize system capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized signal processing is used for DIDO transmissions, then coordination between APs is improved, but network bandwidth requirements and latency increase substantially
Solution Approach 1:
The patent divides the centralized signal processing function into distributed segments at each AP. Each AP independently generates steering matrix information and transmit waveforms locally, eliminating the need to transport raw modulated signals between APs. This segmentation reduces network bandwidth requirements and latency while maintaining coordination through distributed interference nulling.
Solution Approach 2:
The patent introduces a lightweight MAC coordination mechanism as an intermediary that enables APs to share necessary channel state information and coordinate transmissions without requiring full centralized signal processing. This intermediary approach achieves reliable coordination with minimal network overhead and latency.
2Reliability
If more transmit antenna paths are added at each AP to improve receive signal-to-noise ratio, then signal quality improves, but network bandwidth requirements for centralized processing increase substantially
Solution Approach 1:
Each AP independently generates its own steering matrix information and transmit waveforms based on local channel state information. This self-service approach eliminates the need to transport signals through a centralized processor, allowing APs to add transmit antenna paths without increasing network bandwidth requirements for signal transport.
3Productivity
If MU-MIMO techniques are used to transmit to multiple clients simultaneously, then downstream throughput improves, but data rates are lower than single user MIMO due to imperfect nulling and degrees of freedom used for nulling
Solution Approach 1:
The patent changes the approach to multi-client transmission by using distributed interference nulling at each AP rather than centralized MU-MIMO processing. Each AP independently adjusts its steering matrix parameters to null interference to other APs' clients, achieving better nulling performance and higher data rates while maintaining high downstream throughput.
Data Source
AI summary
Techniques are presented for distributed processing Distributed-Input Distributed-Output (DIDO) wireless communication. A plurality of base stations (e.g., APs) are provided, each configured to wirelessly serve one or more wireless devices (e.g., clients). At least first and second base stations are configured to transmit simultaneously at an agreed upon time. The first and second base stations are each configured to locally generate steering matrix information used to spatially precode their respective data transmissions in order to steer their respective data transmissions to their one or more wireless devices while nulling to the one or more client devices of the other base station. Moreover, the first and second base stations are each configured to locally generate a transmit waveform by applying the steering matrix information to their respective data transmissions.