Successive Interference Cancellation for 5G Multi-User Detection
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Solution Overview
Problem
Current 4G wireless communication systems are inadequate to meet the requirements of future 5G systems, particularly in terms of data rates, latency, reliability, and user equipment density, due to limitations in receiver algorithms and antenna configurations.
Innovation Solution
Implementing successive interference cancellation (SIC) using soft decoding information and multi-user MMSE channel estimation to efficiently decode signals from multiple users, allowing for iterative interference cancellation and improved channel estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional 4G receiver algorithms are used, then system complexity is low, but data rates and reliability cannot meet 5G requirements
Solution Approach 1:
The received signal is segmented into multiple user components through iterative detection. The receiver algorithm divides the complex multi-user detection problem into sequential steps: initial detection of one user's signal, cancellation of that signal from the received mixture, then detection of the next user's signal. This segmentation enables high data rates for multiple users while managing computational complexity through structured processing stages.
Solution Approach 2:
The algorithm performs preliminary channel estimation and signal detection for each user before final decoding. By pre-processing the received signal to estimate channel responses and detect transmitted symbols for each user individually, the system prepares cleaned and organized data that meets 5G reliability requirements while keeping the main decoding complexity manageable.
2Reliability
If multi-user signals are detected simultaneously, then processing time is reduced, but interference between users degrades reliability
Solution Approach 1:
The receiver implements periodic iterative detection cycles for each user. In each iteration, the algorithm detects one user's signal, cancels it from the received mixture, then proceeds to detect the next user's signal. This periodic sequential processing eliminates user interference by removing signals step-by-step, achieving 5G reliability requirements while maintaining efficient processing through the structured repetition of detection-cancellation cycles.
3Measurement precision
If iterative interference cancellation is implemented, then multi-user detection accuracy improves, but computational complexity increases
Solution Approach 1:
The iterative interference cancellation process segments the computational task into distinct phases: channel estimation for each user, signal detection, interference reconstruction, and signal subtraction. By dividing the complex multi-user detection into these manageable segments, the algorithm achieves high measurement precision for channel estimation while controlling computational complexity through structured, modular processing steps that can be efficiently implemented.
Data Source
AI summary
An apparatus, such as a base station or a user equipment, includes a transceiver configured to receive a first signal that is a superposition of symbols transmitted concurrently by users in shared resources of an air interface. The apparatus also includes a processor configured to iteratively cancel, for the users, interference produced by the symbols transmitted by other users on the basis of log likelihood ratios (LLRs) that represent likelihoods that previous estimates of the symbols transmitted by the other users are correct. The processor is also configured to iteratively decode the symbols transmitted by the users after canceling the interference produced by the symbols transmitted by the other users.