MIMO Transmission Unit Selection for Capacity and Complexity
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Solution Overview
Problem
In MIMO wireless communication systems, the transmission data capacity is reduced due to high spatial correlation between transmission and reception antennas, leading to error propagation and interference, especially in fading channels with low SINR, where existing techniques like V-BLAST struggle to optimize data streams and power allocation efficiently.
Innovation Solution
The proposed method involves determining transmission units with high channel quality, allocating power only to these units, and using reverse-ordering demodulation to select modulation and coding schemes, thereby concentrating power on fewer transmission units to maximize data capacity while minimizing calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If power is allocated to multiple transmission units in MIMO systems, then transmission diversity is improved, but transmission data capacity is reduced due to high spatial correlation and interference
Solution Approach 1:
The patent extracts and identifies transmission units with high channel quality from the set of all transmission units. By selecting only those units exceeding a quality threshold, the system concentrates power on favorable channels, avoiding the capacity loss caused by transmitting over correlated, low-quality channels. This extraction of high-quality transmission units resolves the contradiction by maintaining diversity through selective transmission while preserving data capacity.
Solution Approach 2:
The patent applies local quality by allocating power non-uniformly across transmission units based on their individual channel quality. Instead of treating all transmission units equally, the system identifies and enhances transmission on units with superior channel conditions, thereby achieving both reliability through targeted diversity and productivity through efficient spectrum utilization in high-quality channels.
2Productivity
If successive symbol estimation and interference cancellation is used, then transmission data capacity is increased, but computational complexity increases
Solution Approach 1:
The patent segments the set of transmission units into two groups: selected units with high channel quality and non-selected units with low channel quality. By processing only the selected units through successive symbol estimation and interference cancellation, the system achieves the capacity benefits of advanced signal processing while significantly reducing computational complexity by excluding poor-quality channels from intensive processing.
Solution Approach 2:
The patent applies partial action by implementing successive symbol estimation and interference cancellation only on a subset of transmission units rather than all units. This selective application provides sufficient capacity enhancement through processing of high-quality channels while avoiding the excessive computational burden of processing all channels, thus resolving the contradiction between productivity and device complexity.
3Productivity
If reverse-ordering demodulation is used, then power allocation efficiency is improved, but modulation and coding scheme determination complexity increases
Solution Approach 1:
The patent inverts the conventional demodulation order by processing transmission units in reverse order of their selection. Instead of determining MCS for all units then selecting, the system selects transmission units first based on channel quality, then determines MCS only for the selected units in reverse order. This inversion improves power allocation efficiency by concentrating power on high-quality channels while reducing overall MCS determination complexity through selective processing.
Data Source
AI summary
An apparatus and method for determining a transmission unit for data stream transmission in a wireless communication system in which multiple transmission and reception antennas are used and a receiver provides information on a data stream to be transmitted through a transmission unit. A fading estimator calculates fading values from the multiple transmission antennas to the multiple reception antennas. A channel quality estimator reverse-orders combined weights for multiple transmission units based on the fading values from the multiple transmission antennas to the multiple reception antennas, successively selects transmission units for data stream transmission among the reverse-ordered transmission units, determines a modulation and coding scheme (MCS) for each of the selected transmission units, and feeds back the MCS to a transmitter.