Random Beamforming Interference Control in Wireless Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Communication systems with multiple base stations face interference issues that decrease throughput, and existing interference control and alignment technologies increase overhead, necessitating optimized methods to enhance radio resource usage efficiency.
Innovation Solution
A method involving terminals generating decoding matrices to extract desired signals from serving base stations, considering interference from neighboring base stations, and feeding back signal quality information to select optimal communication pairs, using techniques like zero-forcing or maximum SINR decoding schemes, and randomly determining precoding matrices to reduce overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If interference control technologies or interference alignment technologies are used, then interference is reduced and throughput is enhanced, but overhead increases
Solution Approach 1:
Each terminal independently generates its own decoding matrix based on locally estimated interference from neighboring base stations, without requiring centralized coordination or extensive channel information sharing. The terminal autonomously performs interference alignment and selects optimal communication pairs based on local SINR calculations, eliminating the need for complex system-wide coordination protocols.
Solution Approach 2:
The invention extracts only the essential interference information (interference covariance matrix) that each terminal needs to perform decoding, separating this from the complete channel state information. By taking out only the necessary interference characteristics rather than sharing all channel details, the system reduces overhead while maintaining interference control effectiveness.
2Measurement precision
If decoding matrices are generated based on interference from neighboring base stations, then desired signal extraction is improved, but calculation complexity increases
Solution Approach 1:
The terminal generates decoding matrices based on interference from only the neighboring base stations that are most relevant to its current communication needs, rather than processing interference from all possible base stations. This partial action approach reduces calculation complexity while maintaining sufficient signal extraction quality for practical communication scenarios.
Data Source
AI summary
Provided is a communication system using various types of random beamforming technologies. Each of terminals that belong to a user group may generate a decoding matrix, based on interference caused by a neighboring base station of a serving base station. Each of the terminals may transmit, to the serving base station or the neighboring base station, information associated with a signal-to-interference plus noise ratio (SINR) or throughput based on the decoding matrix. The serving base station may select, from the terminals, at least one target terminal to communicate with the serving base station.