L1-Norm Sphere Detector for MIMO Signal Decoding
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Solution Overview
Problem
Existing MIMO wireless communication systems face complexity and computational expense in decoding signals due to the use of L2-Norm transformations, which can be reduced by employing L1-Norm transformations without compromising performance.
Innovation Solution
Implementing a sphere detector in MIMO receivers that uses L1-Norm transformations, specifically generating candidate lists with L1-Norm error metrics and applying scaling factors like expected value scaling or MMSE scaling to achieve reduced computational complexity and improved performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If L2-Norm transformations are used in MIMO signal decoding, then decoding accuracy is maintained, but computational complexity and circuit complexity increase
Solution Approach 1:
The patent changes the norm parameter from L2-Norm to L1-Norm in the error metric calculation. This parameter change transforms the mathematical operation from squared Euclidean distance to Manhattan distance, reducing the number of multiplication operations required while maintaining acceptable decoding performance within 0.5 dB of L2-Norm methods
Solution Approach 2:
The patent employs simpler computational operations (addition and absolute value) that are cheaper and more resource-efficient compared to the multiplication-intensive L2-Norm operations. This substitution reduces hardware resource requirements and circuit complexity while achieving comparable performance
2Reliability
If L2-Norm squared values are used in sphere detection, then performance is optimized, but the number of multiplication operations increases
Solution Approach 1:
The patent changes the error metric parameter from L2-Norm squared to L1-Norm, fundamentally altering the computational operations required. The L1-Norm uses only addition and absolute value operations, eliminating the need for multiplication operations that are computationally expensive and energy-intensive
Solution Approach 2:
The patent substitutes the multiplication-based L2-Norm calculation mechanism with an addition-based L1-Norm calculation mechanism. This substitution replaces complex arithmetic operations with simpler ones, reducing computational expense and energy consumption while maintaining performance within 0.5 dB
3Device complexity
If L1-Norm transformations are used in MIMO receivers, then computational complexity is reduced, but performance may be compromised
Solution Approach 1:
The patent applies L1-Norm transformation with specific scaling factors (expected value scaling or MMSE scaling) to the error metric. This parameter adjustment ensures that the simplified L1-Norm calculation achieves performance within 0.5 dB of the more complex L2-Norm methods, effectively resolving the performance concern
Data Source
AI summary
A method of processing a signal within a receiver can include generating, using the receiver, a candidate list including at least one entry for a signal. Each entry can include a candidate symbol vector and an L1-Norm error metric. The method can include, for each entry, generating an L1-Norm transformation from the L1-Norm error metric, wherein the L1-Norm transformation depends upon a function of a number of receiving antennas of the receiver. The signal can be decoded using the candidate list including the L1-Norm transformations.