MIMO Precoder Optimization for Wireless Multicast Efficiency
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Solution Overview
Problem
Current wireless communication systems employing MIMO schemes face inefficiencies in spectral usage when broadcasting or multicasting data, particularly due to suboptimal pre-coding and resource allocation, which can lead to reduced spectral efficiency and increased power consumption.
Innovation Solution
A method is introduced that optimizes pre-coders and resource units for transmitting public data to multiple terminals using a MIMO scheme, where optimized pre-coders and resource units are determined based on channel quality feedback to adapt transmission to the instantaneous conditions of each terminal, enhancing spectral efficiency and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional broadcast transmission with fixed pre-coders is used, then implementation simplicity is maintained, but spectral efficiency deteriorates due to inability to adapt to instantaneous channel conditions
Solution Approach 1:
The patent applies dynamics by transitioning from fixed pre-coders to dynamic pre-coder selection. The base station determines optimized pre-coders and resource unit quantities based on instantaneous channel quality information from multiple terminals, allowing the transmission parameters to adapt dynamically to changing channel conditions, thereby improving spectral efficiency
Solution Approach 2:
The patent changes transmission parameters (pre-coders and resource unit quantities) based on channel quality feedback. By selecting from multiple candidate pre-coders and adjusting resource unit allocation dynamically, the system optimizes transmission parameters to match instantaneous channel conditions, resolving the contradiction between adaptability and complexity
2Reliability
If unicast mode is used for each terminal, then individual channel quality optimization is achieved, but spectral efficiency deteriorates due to redundant transmission of same data to multiple terminals
Solution Approach 1:
The patent merges the benefits of unicast (channel quality adaptation) with multicast (resource sharing). By determining a single set of optimized pre-coders and resource unit quantities that satisfy multiple terminals' channel conditions, the system combines unicast-level optimization with multicast efficiency, avoiding redundant transmissions while maintaining reliability
Solution Approach 2:
The patent creates a universal transmission scheme that serves multiple terminals simultaneously with optimized pre-coders. The determined pre-coders and resource unit quantities are universally applicable to all K terminals in the multicast group, achieving channel quality adaptation for each terminal while maintaining spectral efficiency through shared resource allocation
3Productivity
If more pre-coders are used for optimization, then transmission capacity is improved, but computational complexity increases
Solution Approach 1:
The patent segments the large set of candidate pre-coders into a manageable subset of N optimized pre-coders. By selecting and optimizing only the most relevant pre-coders for the current channel conditions rather than evaluating all possible pre-coders, the system reduces computational complexity while maintaining high transmission capacity
Solution Approach 2:
The patent applies partial action by determining optimized pre-coders and resource unit quantities for only the necessary number of data streams (N′≤N) rather than optimizing all possible transmissions. This selective optimization approach achieves sufficient transmission capacity while limiting computational complexity to what is truly necessary
Data Source
AI summary
The invention relates to the transmitting of a public data to at least a number K of terminals in a wireless communication system employing a MIMO (Multiple Input Multiple Output) scheme, using a set of N pre-coders (Wi). The method includes, based on the N pre-coder (Wi), determining a set of N′≤N optimized pre-coders (W′i) and, based on the set of N′≤N optimized pre-coders (W′i), computing N′ optimized resource unit quantities T′(i), the N′ optimized pre-coders respectively corresponding to the N′ optimized resource units quantities T′(i). The method further includes transmitting N′ data Di, each of the N′ data being a part of the public data, such that, for i=1 to N′, Di is transmitted on T′(i) resource units which are pre-coded onto NTx antennas using the pre-coder W′i.