Iterative MIMO Detection for CDMA Interference Subtraction
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Solution Overview
Problem
Existing digital communication systems face challenges in decoding digital data on frequency-selective MIMO channels due to cumulative interference from spatial multi-antenna interference, intersymbol interference, and multi-user interference, which limits capacity and requires complex processing.
Innovation Solution
An iterative decoding and equalization device with a bank of linear filters for each user, interference subtraction, and external decoding to generate probabilistic information, effectively handling MAI, ISI, and MUI interference in a multicode CDMA transmission system without channel state information at the sender.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If maximum likelihood detection is used to achieve optimal performance, then detection accuracy is improved, but computational complexity increases significantly
Solution Approach 1:
The detection process is segmented into multiple iterative stages: initial linear detection, interference regeneration, interference subtraction, and refined detection. Each stage processes a portion of the interference separately, transforming the single complex ML detection into multiple simpler detection stages that collectively approach ML performance.
Solution Approach 2:
The interference from other users and antennas is regenerated and subtracted before the final detection stage. This preliminary interference cancellation prepares the signal by removing dominant interference components, allowing the subsequent detection to operate on a cleaner signal with reduced complexity requirements.
2Reliability
If iterative interference cancellation is implemented to reduce interference, then signal quality is improved, but processing complexity increases
Solution Approach 1:
The system performs partial interference cancellation by regenerating and subtracting only the dominant interference components (multi-user interference and spatial interference) rather than attempting to cancel all interference perfectly. This partial action achieves significant signal quality improvement while keeping processing complexity manageable.
Solution Approach 2:
The detected symbols are fed back into the interference regeneration stage, where they are used to reconstruct and subtract interference. This feedback loop iteratively improves signal quality by using previously detected information to cancel interference in subsequent detection stages.
3Productivity
If the number of users exceeds the number of antennas (overloaded system), then system capacity is improved, but multi-user interference increases
Solution Approach 1:
The multi-user interference, which normally degrades performance, is converted into a beneficial signal by regenerating it from detected symbols and subtracting it from the received signal. The harmful interference is transformed into a known component that can be removed, allowing the system to support more users than antennas while maintaining performance.
4Productivity
If frequency-selective MIMO channel is used to increase data rate, then spectral efficiency is improved, but interference from intersymbol interference increases
Solution Approach 1:
The frequency-selective channel response is segmented into multiple taps representing different propagation paths and delays. Each tap is processed separately through the interference cancellation and detection stages, allowing the system to handle intersymbol interference from different time delays independently and reconstruct the original symbols with reduced ISI effects.
Data Source
AI summary
The invention relates to a reception method for communication over frequency-selective channels with a plurality of send antennas and a plurality of receive antennas, to process data received by the receive antennas that, on sending, was successively modulated and spread.To this end, reception uses:linear filtering (202, 202′) adapted to process the received data to generate an evaluation (Ŝ) of the sent modulated data before spreading, this filtering taking account in particular of the spatial diversity of the plurality of receive antennas;subtracting interference using an estimate of multi-antenna interference (MAI), intersymbol interference (ISI), and multi-user interference (MUI) previously regenerated on the basis of the evaluation (ŝ) of the sent modulated data generated by previous filtering 202; processing to generate an interference estimate for the data received from information computed on the basis of the evaluation (ŝ) of the sent modulated data.The invention relates further to a reception system adapted to implement the method and a transmission system including the reception system.