MIMO SIC Decoding Order for Global Interference Cancellation Gain
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Solution Overview
Problem
Conventional successive interference cancellation (SIC) methods in multiple input multiple output (MIMO) systems do not always optimize the decoding order of codewords to maximize interference cancellation gain, often assuming perfect interference cancellation and resulting in suboptimal performance.
Innovation Solution
The method determines a globally optimal decoding order for codewords by computing performance objectives for various orderings, using techniques such as tree representations to reduce complexity and predict performance components from channel information, ensuring that the codewords are decoded in an order that maximizes the overall performance objective.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional SIC methods decode codewords based on channel parameters at each stage, then locally optimal decoding order is achieved, but globally optimal interference cancellation gain is not guaranteed
Solution Approach 1:
The patent pre-calculates and stores performance metrics (such as signal-to-interference-plus-noise ratio) for all possible codeword orderings before the actual decoding process. This preliminary action allows the system to quickly retrieve and compare pre-computed performance data during operation, avoiding the need for complex real-time optimization while achieving globally optimal decoding order selection.
Solution Approach 2:
The patent dynamically adapts the decoding order based on actual channel conditions by computing performance metrics for different orderings and selecting the optimal one. Rather than using a fixed or locally optimal ordering, the system dynamically evaluates multiple possible orderings and adjusts the decoding sequence to maximize overall interference cancellation gain according to current system state.
2Reliability
If all possible codeword orderings are evaluated to find globally optimal decoding order, then maximum interference cancellation gain is achieved, but computational complexity increases
Solution Approach 1:
The patent segments the evaluation of codeword orderings by dividing the set of all possible permutations into manageable groups or stages. Rather than evaluating all N! permutations simultaneously, the system processes orderings in a structured sequence, evaluating subsets of orderings at each stage and using intermediate results to guide subsequent evaluations, thereby reducing peak computational requirements.
Solution Approach 2:
The patent evaluates a sufficient subset of codeword orderings that achieves near-optimal interference cancellation without exhaustively evaluating all possible permutations. By identifying and evaluating only the most promising orderings based on preliminary channel condition assessments, the system achieves adequate performance with reduced computational effort compared to complete enumeration.
Data Source
AI summary
Systems and methods are provided for determining a successive interference cancellation (SIC) decoding ordering in a multiple input multiple output transmission (MIMO) system. Multiple decoding orderings for received codewords are identified. A performance objective, such as total throughput or total probability of decoding, is computed for each one of the orderings based on the position of the codewords in the ordering. A globally optimal ordering is found that maximizes the performance objective over the multiple decoding orderings.