NQAM Resource Allocation for Non-Gaussian Interference Channels
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Solution Overview
Problem
Current wireless communication systems face limitations in forming non-Gaussian interference channels due to high complexity in non-binary encoding/decoding technologies, which restricts their ability to achieve optimal network throughput and channel capacity.
Innovation Solution
The method involves determining modulation order, code rate, and resource allocation based on channel quality and non-Gaussian information, using a Nulling Quadrature Amplitude Modulation (NQAM) scheme that activates unused subcarriers and applies different permutation rules for each cell, thereby reducing complexity and forming a non-Gaussian interference channel with binary codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If non-binary encoding/decoding technology is applied to achieve non-Gaussian interference channel, then network throughput and channel capacity are improved, but system complexity becomes very large
Solution Approach 1:
The patent segments the interference channel into multiple independent subchannels through eigenmode decomposition. Instead of treating the entire MIMO channel as a single complex non-Gaussian interference problem, the system decomposes it into parallel subchannels that can be handled independently with simpler binary encoding/decoding, thus reducing overall system complexity while maintaining throughput benefits.
Solution Approach 2:
The patent introduces an intermediary preprocessing stage that transforms the received signal before decoding. By applying linear transformation and interference cancellation as intermediate steps, the system converts the complex non-Gaussian interference problem into a series of simpler Gaussian-like subproblems that can be solved with standard binary encoding/decoding techniques.
2Productivity
If FQAM modulation scheme is applied to users at cell boundary, then non-Gaussian interference channel is formed and spectral efficiency is improved, but implementation complexity increases
Solution Approach 1:
Instead of applying complex non-binary encoding to achieve non-Gaussian characteristics, the patent inverts the approach by using simple binary encoding with intelligent resource allocation and interference management. The system achieves non-Gaussian interference channel benefits through the inversion of the conventional wisdom, proving that complex modulation is not necessary if proper resource allocation is implemented.
Solution Approach 2:
The patent changes the allocation parameters of resource blocks to specific users based on channel conditions and interference levels. By dynamically adjusting which users receive which resource blocks and how they are configured, the system creates non-Gaussian interference patterns without requiring complex FQAM modulation, thus achieving spectral efficiency improvements with reduced complexity.
3Device complexity
If QAM modulation is used to approximate Gaussian interference, then system operation with low complexity is achieved, but network throughput is limited
Solution Approach 1:
The patent makes the resource allocation system universal by creating a framework that can adapt to different channel conditions and user requirements. The same binary encoding/decoding infrastructure is used universally across all users, but the resource block allocation and interference management are dynamically adjusted to achieve non-Gaussian characteristics when beneficial, thus maintaining low complexity while enabling throughput improvement when conditions permit.
Data Source
AI summary
The present disclosure relates to a pre-5th-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4th-Generation (4G) communication system such as Long Term Evolution (LTE). Provided is an operation method of a base station in a wireless communication system. The method comprises: receiving, from a terminal, at least one piece of information among channel quality information on a resource region allocated to the terminal and non-Gaussian information on a nulling region corresponding to the resource region; and determining a modulation order for the terminal, a code rate, a ratio of the resource region to the nulling region based on the channel quality information and the non-Gaussian information.