MIMO-OFDM Signal Estimation via EM Iterative Algorithm
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Solution Overview
Problem
Conventional MIMO-OFDM systems face challenges in accurately estimating channel signals due to multipath fading, especially when using QAM-modulated and space-time block coded signals, as existing methods require statistical data and are difficult to implement in actual systems.
Innovation Solution
An EM-based iterative estimation algorithm is employed to estimate signal sequences without producing an inverse matrix, using normalized values of received signals on a channel-by-channel basis, which compensates for signal distortion caused by multipath fading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional channel estimation methods (deterministic ML or MMSE) are used, then channel estimation can be performed, but implementation difficulty increases due to requirement of statistical data and complex calculations
Solution Approach 1:
The patent changes the estimation approach from direct statistical methods to an iterative parameter refinement method. It transforms the channel estimation problem into finding parameters that maximize the likelihood function, using iterative updates of estimation values rather than direct computation requiring statistical data
Solution Approach 2:
The patent introduces an intermediary likelihood function as a mediator between the received signal and channel estimation. Instead of directly estimating channels from statistical data, the method uses the likelihood function as an intermediate step that guides the iterative estimation process, making implementation more feasible
2Measurement precision
If inverse matrix calculations are performed at each iteration time, then sequence estimation can be updated, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent performs preliminary decomposition of the matrix into eigenvalues and eigenvectors before the iterative process begins. This preliminary action allows subsequent iterations to use pre-computed components rather than performing full inverse matrix calculations each time, significantly reducing processing time while maintaining estimation accuracy
Solution Approach 2:
The patent replaces the mechanical computation of inverse matrices with an eigenvalue-based computational approach. By substituting the direct inverse operation with operations on eigenvalues and eigenvectors, the method reduces computational complexity from O(n³) to O(n²) or better in each iteration
3Measurement precision
If statistical data is used for channel estimation, then estimation can be performed, but system adaptability decreases due to difficulty in obtaining accurate statistical information in actual systems
Solution Approach 1:
The patent enables the system to estimate channels without relying on external statistical data by using self-service iterative refinement. The algorithm uses the received signal itself and progressively improves estimation accuracy through multiple iterations, making the system adaptable to various channel conditions without requiring pre-known statistical information
Data Source
AI summary
A apparatus and method for estimating a sequence of transmitted quadrature amplitude modulation (QAM)-modulated signals and space-time block coded signals using an optimal expectation-maximization (EM)-based iterative estimation algorithm in a multiple-input and multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) mobile communication system. An initial sequence estimation value is produced on the basis of a predetermined initial value using a pilot sub-carrier contained in each of OFDM signals received by a receiving side. A normalized value of a received signal on a channel-by-channel basis is produced by a predetermined equation using orthogonality between the OFDM signals received by the receiving side. At least one subsequent sequence estimation value is produced using the initial sequence estimation value and the normalized value of the received signal on the channel-by-channel basis. If the subsequent sequence estimation value converges to a constant value after an operation of producing the subsequent sequence estimation value is iterated the predetermined number of times, the converged subsequent sequence estimation value is designated as a final sequence estimation value.