MMSE-SIC Equalizer With Fixed-Matrix Weights for Lower Power
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Solution Overview
Problem
Integrated circuits (ICs) used in MIMO OFDM systems for high data rate wireless communication face significant challenges in reducing power consumption, which is exacerbated by the increasing complexity of circuit designs and the demand for programmable resources.
Innovation Solution
An equalizer for minimum mean-square-error successive-interference-cancellation (MMSE-SIC) is implemented, which uses fewer circuit resources by employing a demodulator and decoder with iterative processing loops, a detection-cancellation block, a channel pre-processor block, and a log-likelihood-ratio determination block, and approximates weight vectors using a fixed matrix to reduce power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional demodulators with full MMSE-SIC processing are used, then power consumption increases, but circuit resource utilization increases
Solution Approach 1:
The demodulator is divided into distinct functional blocks: detection-cancellation block for interference removal, channel pre-processor block for weight calculation, and log-likelihood-ratio determination block for decision-making. This segmentation allows selective processing and reduces overall power consumption by enabling independent optimization of each block.
Solution Approach 2:
The system performs partial MMSE-SIC processing by iteratively processing only a subset of received signals in each iteration rather than processing all signals fully. The detection-cancellation block selectively cancels interference from dominant signals, and the process repeats for remaining signals, reducing computational load and power consumption while maintaining acceptable performance.
2Measurement precision
If iterative demodulating-decoding sequences are implemented, then processing accuracy improves, but computational complexity increases
Solution Approach 1:
The demodulator and decoder are coupled to form iterative feedback loops where the decoder provides feedback information to the detection-cancellation block, which refines interference cancellation estimates for the next iteration. This feedback mechanism progressively improves processing accuracy by incorporating decoded information to enhance subsequent detection and cancellation operations.
Solution Approach 2:
The channel pre-processor block pre-calculates weight vectors using a fixed matrix approximation before the main iterative processing begins. This preliminary action reduces the computational burden during iterative sequences by preparing processing parameters in advance, thereby improving accuracy without proportionally increasing computational complexity during the iterative phase.
3Use of energy by moving object
If fixed matrix approximation is used for weight vectors, then power consumption decreases, but processing precision may be affected
Solution Approach 1:
The system changes the parameter representation of weight vectors by using a fixed matrix approximation instead of calculating full MMSE weight vectors dynamically. This parameter change reduces computational requirements and power consumption while the iterative feedback process compensates for the approximation error, maintaining acceptable processing precision through progressive refinement across multiple iterations.
Data Source
AI summary
In an embodiment of an equalizer, a demodulator for MMSE-SIC receives a symbol vector to provide first information. A decoder receives the first information to provide second information to the demodulator. The decoder iteratively processes the first information to provide the second information. The demodulator and decoder are coupled in a loop for feeding back the second information for iteratively refining the first information. A detection-cancellation block of the demodulator receives the symbol vector to provide an equalized vector. A channel pre-processor block of the demodulator receives an initial vector output of the detection-cancellation block for the symbol vector for a demodulating-decoding iterative sequence to provide a weight vector. The channel pre-processor block provides an approximation using a fixed matrix to generate the weight vector. The detection-cancellation block receives the weight vector for equalization of the symbol vector in order to provide the equalized vector.