Noise-Aware Receiver for Overloaded Wireless Systems
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Solution Overview
Problem
Existing digital wireless systems face challenges in estimating symbols from a discrete digital signaling alphabet in noisy environments, particularly in overloaded scenarios where the number of transmitters exceeds the number of receivers, leading to complex signal detection and high computational costs.
Innovation Solution
A noise-aware receiver design that incorporates noise effects into the signal detection process using an adaptive l0-norm approximation and fractional programming, transforming the intractable l0-norm minimization into a sequence of convex problems, thereby reducing noise amplification and improving detection performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional signal detection methods are used in overloaded channels, then the system can handle more transmitters, but the computational complexity increases exponentially
Solution Approach 1:
The patent transforms the l0-norm minimization problem into a sequence of convex problems by changing the mathematical parameters and formulation approach. This allows the system to handle overloaded channels with polynomial-time complexity rather than exponential complexity, resolving the contradiction between handling more transmitters and maintaining computational feasibility.
2Measurement precision
If l0-norm minimization is used for exact discrete signal recovery, then detection accuracy is improved, but the problem becomes intractable
Solution Approach 1:
The patent segments the intractable l0-norm minimization problem into a sequence of tractable convex subproblems. By breaking down the original optimization problem into manageable convex steps, the system achieves exact discrete signal recovery without encountering computational intractability.
Solution Approach 2:
The patent introduces convex relaxation as an intermediary approach between the intractable l0-norm minimization and practical solution. This intermediary formulation allows the system to approximate the discrete signal recovery problem in a computationally feasible manner while maintaining accuracy.
3Device complexity
If standard receivers are used in noisy environments, then the system structure is simple, but noise amplification degrades detection performance
Solution Approach 1:
The patent converts the harmful effect of noise by incorporating noise-aware processing into the detection algorithm. Rather than simply filtering noise, the system uses noise statistics to improve detection performance, transforming the noise problem into a benefit for achieving better bit error rate performance.
Data Source
AI summary
A computer-implemented reconstruction method of discrete digital signals in noisy overloaded wireless communication systems that is characterized by a channel matrix of complex coefficients, the method including, receiving the signal from channel by a signal detector, measuring the noise power by a noise power estimator at the receiver, forwarding the detected signal and noise power estimation to a decoder that estimates the transmitted symbol, wherein the estimation of the decoder produces a symbol that could probably have been transmitted it is forwarded to a de-mapper, which outputs the bit estimates corresponding to the estimated transmit signal and the corresponding estimated symbol to a microprocessor for further processing.