Non-Coherent Wireless Communication via Basis Expansion Model
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Solution Overview
Problem
Current wireless communication systems face challenges in transmitting high-speed data through doubly-selective channels, particularly in mobile networks, due to time-varying fading and multi-path delays, which cause inter-carrier interference (ICI) and inter-symbol interference (ISI), and require pilot symbols for channel estimation, leading to reduced spectral efficiency and complexity.
Innovation Solution
A method for non-coherent wireless communications using a multi-dimensional basis expansion model (BEM) with generalized likelihood ratio test (GLRT) equalization, which accounts for timing and carrier offsets without relying on pilot symbols, employing Legendre polynomial and Fourier exponential basis functions to handle doubly-selective fading channels and mitigate ICI and ISI.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pilot symbols are inserted for channel estimation, then channel state information can be obtained for equalization, but spectral efficiency and data transmission rate are reduced
Solution Approach 1:
The system uses the transmitted data symbols themselves to estimate channel state information through basis expansion modeling, eliminating the need for separate pilot symbols. The data symbols serve dual purposes: carrying information and enabling channel estimation, thus achieving self-service and maintaining spectral efficiency.
Solution Approach 2:
The transmitted symbols perform multiple functions simultaneously: they carry data information and provide channel estimation information. By using basis expansion models, the same signal resources are utilized for both communication and channel sensing, achieving multi-functionality without requiring additional pilot resources.
2Measurement precision
If pilot symbols are used for channel estimation in doubly-selective channels, then some CSI can be obtained, but the system complexity increases and performance degrades due to ICI and ISI
Solution Approach 1:
The system transforms the channel estimation problem by changing the representation parameters from time-domain pilot-based estimation to frequency-domain basis expansion coefficients. This parameter transformation simplifies the estimation process in doubly-selective channels by converting a complex time-varying problem into a more manageable coefficient estimation problem.
Solution Approach 2:
Basis expansion models serve as an intermediary representation that bridges the transmitted signal and channel state information. Instead of directly estimating complex instantaneous CSI from corrupted received signals, the system estimates basis expansion coefficients that indirectly represent the channel characteristics, simplifying the estimation process.
3Productivity
If BEM is used to approximate singly-selective fading channels, then semi-blind transmissions can be realized, but the method still relies on pilot symbols for initial CSI estimation and FEC feedbacks
Solution Approach 1:
Instead of using pilot symbols to initialize channel estimation and then processing FEC feedbacks through complex iterative algorithms, the system inverts the approach by directly estimating basis expansion coefficients from data symbols without pilots. This eliminates the need for initial pilot-based initialization and simplifies the receiver structure.
Solution Approach 2:
The invention extracts and eliminates the unnecessary components of the semi-blind transmission system: pilot symbols for initial estimation and complex FEC soft-decision decoding feedback loops. By removing these elements while retaining the core BEM functionality, the system achieves simplified non-coherent transmission.
4Productivity
If DSTC is used for non-coherent communications, then spectral efficiency is maintained without pilot symbols, but performance degrades in fast time-varying channels with short coherence time
Solution Approach 1:
The system transitions from static Grassmannian orthogonal matrices used in traditional DSTC to dynamic basis expansion models that adapt to fast time-varying channels. The basis expansion approach dynamically captures channel variations through time-varying coefficients, maintaining reliability in fast fading while preserving the pilot-free spectral efficiency of non-coherent methods.
Data Source
Figure 1
Figure 2A~2B
Figure 3A
AI summary
A method for decoding data symbols modulated with a corresponding codeword from a constellation set of codewords expands the constellation set of codewords with a set of basis functions to produce a basis-expanded constellation set and projects projecting a received modulated data symbol onto orthogonal complements of the basis expanded constellation set to obtain a set of distance metric of a generalized likelihood ratio test (GLRT) for each codeword of the constellation set. The set of basis functions includes a Fourier exponential basis function in a frequency domain, a Legendre polynomial basis function in a time domain, and a Fourier-Legendre product basis function in the frequency domain. The method selects a codeword corresponding to a minimal distance metric or a maximal correlation metric and decodes the data symbol from the received modulated data symbol using the codeword.