MIMO Decoder Precomputation Logic for Power Reduction
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Solution Overview
Problem
The complexity of decoding in Spatial Multiplexing MIMO wireless communication systems is high due to the need to solve systems of equations at fast data rates, which requires significant processing resources and power consumption, especially in systems like 4×4 SM-MIMO with 16-QAM or 64-QAM, where conventional decoders like MLD and QRD-M SM decoder still have high complexity.
Innovation Solution
The implementation of precomputation logic to reduce power consumption by eliminating redundant distance computations in the M-algorithm of the QRD-M SM decoder, using predictor functions to control the processing stages and only perform computations on symbol sequences expected to generate the minimum cumulative distance metric, thereby reducing internal switching activity and critical path delay.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional decoders (MLD or QRD-M) are used in Spatial Multiplexing MIMO systems, then decoding functionality is provided, but the complexity of decoding remains high and power consumption is significant
Solution Approach 1:
The patent applies preliminary action by precomputing distance metrics for the first stage of the M-algorithm before actual decoding operations. The distance computation unit calculates and stores distance metrics for all possible symbol sequences in the first stage, which are then reused during decoding. This precomputation eliminates redundant calculations during real-time operation, significantly reducing both decoding complexity and power consumption while maintaining accurate distance metric comparisons for symbol sequence selection.
2Productivity
If fast data rate decoding is implemented to meet high throughput requirements, then productivity increases, but processing resource requirements and power consumption increase
Solution Approach 1:
The patent implements preliminary action by precomputing and storing distance metrics for the first stage symbol sequences before decoding operations begin. The distance computation unit calculates these metrics in advance and stores them in memory, allowing the decoder to rapidly retrieve and compare precomputed values during high-speed operation. This eliminates the need for repeated calculations during real-time decoding, enabling fast throughput while reducing power consumption by avoiding redundant computational operations.
3Measurement precision
If complete distance computations are performed for all symbol sequences in the M-algorithm, then measurement precision is maintained, but the number of computations and processing time increase
Solution Approach 1:
The patent applies preliminary action by precomputing distance metrics for all first-stage symbol sequences and storing them for rapid retrieval. This precomputation ensures that accurate distance metrics are available without performing complete calculations during real-time decoding. The stored metrics maintain measurement precision while dramatically reducing processing time, as the decoder only needs to retrieve and compare precomputed values rather than recalculate them for each symbol sequence evaluation.
Data Source
AI summary
Spatial Multiplexing (SM) with Multiple Input Multiple Output (MIMO) is used in many communication systems for providing high data rates. While SM-MIMO is a powerful technique for increasing the data rate and bandwidth efficiency, the decoders for SM-MIMO are highly complex. The complexity grows exponentially for optimum decoders as the number of multiplexed layers in SM-MIMO increases. Many reduced complexity suboptimal methods are used in practice that have close to optimum performance but they remain highly complex causing high power consumption which is not desirable for battery operated client terminals. Due to the parallel architecture of many of the SM-MIMO decoders, they involve computations that may eventually turn out to be redundant. A method and apparatus may include identifying and eliminating potentially redundant computations in SM-MIMO decoders based on the technique referred herein as precomputation. The removal of redundant computations enables reduced power consumption for SM-MIMO decoders.