Uplink NOMA Cell-Free MIMO Detection Using Iterative Message Passing
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Solution Overview
Problem
In cell-free MIMO networks, effectively distinguishing and detecting uplink signals from multiple user equipments (UEs) is challenging due to non-orthogonal multiple access, where signals from different UEs mix and overlap, complicating the decoding process.
Innovation Solution
A method involving a factor graph-based message passing algorithm (MPA) is employed, where access points (APs) estimate the probability of symbols transmitted by UEs, and iteratively refine these estimates through message passing with UEs, utilizing a constellation truncation technique to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If non-orthogonal multiple access is used to enable simultaneous access by multiple UEs, then system throughput is improved, but signal detection becomes more difficult due to signal mixing and overlap
Solution Approach 1:
The patent segments the detection process into multiple iterative steps using message passing between APs and UEs. Each iteration refines the probability estimates for transmitted symbols by dividing the complex detection problem into smaller, manageable sub-problems that are solved sequentially until convergence is achieved.
Solution Approach 2:
The patent introduces probability estimates as an intermediary mechanism between signal reception and final detection. Instead of directly detecting symbols from mixed signals, the system uses iterative probability refinement as a mediator to gradually separate and identify individual UE transmissions within the non-orthogonal signal mixture.
2Measurement precision
If iterative message passing algorithms are used to improve symbol detection accuracy, then detection precision is improved, but computational complexity increases
Solution Approach 1:
The patent applies partial action by performing message passing iterations only between connected APs and UEs rather than all possible pairs. The algorithm performs a sufficient number of iterations to achieve adequate detection accuracy without unnecessarily continuing until complete convergence, thus balancing precision with computational complexity.
3Measurement precision
If constellation truncation technique is applied to enhance detection accuracy, then measurement precision is improved, but information loss occurs due to truncation
Solution Approach 1:
The patent applies preliminary action by performing constellation truncation before the full iterative detection process. By pre-selecting and truncating the constellation based on initial probability estimates, the system reduces the search space and computational burden for subsequent iterations, achieving efficient detection while minimizing information loss through the preliminary filtering step.
Data Source
AI summary
In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus for wireless communication are provided. The method comprising: receiving a signal transmitted by a set of user equipments (UEs); estimating, for a first UE in the set of UEs, a first-probability set for one or more symbols transmitted by the first UE; providing, to a first set of APs which received the one or more symbols transmitted by the first UE, the first-probability set; and receiving, from the first set of APs, a second-probability set for the one or more symbols transmitted by the first UE.