Interference Mitigation in Single-User Coded Signal Detection
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Solution Overview
Problem
Communications systems face increased bit- and symbol-error rates due to interference from other transmitters in wireless and wired channels, such as cellular and DSL systems, where coordination between transmitters and receivers is absent, leading to degraded signal quality and decoding performance.
Innovation Solution
The implementation of a symbol-by-symbol joint maximum-likelihood detector and an AWGN-based detector to mitigate interference by treating interference and noise as Gaussian noise, allowing for the decoding of message bits from received symbols in the presence of interference, using techniques like filtering and constellation point determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional detectors are used in interference channels, then device complexity remains low, but bit-error rate and symbol-error rate increase due to interference from secondary transmitters
Solution Approach 1:
The detector processes symbols one at a time in sequence, dividing the complex task of detecting multiple overlapping signals into separate sequential detection steps. Each symbol is detected independently after filtering, reducing the complexity of simultaneous multi-symbol detection while maintaining accuracy in the presence of interference.
Solution Approach 2:
A filter is introduced as an intermediary component between the received signal and the detection process. The filter processes the received symbols to create filtered symbols that are then used for constellation point determination, simplifying the detection task by pre-processing the signal to reduce interference effects.
2Measurement precision
If joint maximum-likelihood detection is implemented to handle interference, then decoding accuracy improves, but computational complexity increases
Solution Approach 1:
The joint detection process is segmented into sequential symbol-by-symbol detection steps rather than simultaneous detection of all symbols. This segmentation reduces the computational burden at each step while maintaining overall detection accuracy through the filtered symbol processing approach.
Solution Approach 2:
The detector changes the representation of the received signal by transforming it into filtered symbols with modified constellation points. This parameter transformation simplifies the detection problem by reparameterizing the signal space to account for interference effects, reducing computational complexity while maintaining accuracy.
3Device complexity
If interference is treated as Gaussian noise using AWGN-based detection, then detector design is simplified, but performance degrades when interference is strong and non-Gaussian
Solution Approach 1:
The detector changes the statistical model by transforming the received signal through filtering to create a representation where interference and noise are combined into an effective Gaussian noise term. This parameter transformation allows the use of simple AWGN-based detection algorithms while maintaining performance in interference channels through the filter design.
Data Source
AI summary
Techniques are provided for detecting a coded signal in the presence of interference. In an embodiment, a primary transmitter corresponds to a desired transmitter, and one or more secondary transmitters correspond to interfering transmitters. Received symbols, which include interference and additive noise, are filtered to recover a set of original message bits. An estimate of the set of original message bits may be determined using an ordered successive interference cancellation (SIC) decoder that uses either a SIC detector or an AWGN-based detector, depending on the signal-to-interference ratio at a primary receiver.