MIMO-OFDM Link Adaptation Using Effective SINR for AMC
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Solution Overview
Problem
Existing MIMO-OFDM systems face challenges in applying adaptive modulation and coding (AMC) due to the complexity of maximum likelihood detection (MLD) and channel estimation errors, leading to performance loss and inefficiencies in data transmission.
Innovation Solution
Implementing a near-MLD performance algorithm with calibration methods to estimate channel quality using received bit mutual information rate (RBIR) and calculating effective SINR through upper and lower bounds, accounting for channel orthogonality ratios to enhance AMC in MIMO systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maximum likelihood detection (MLD) is used for optimal data estimation in MIMO systems, then detection performance is improved, but computational complexity increases exponentially
Solution Approach 1:
The patent transforms the non-linear MLD problem into a linear effective SINR calculation problem by changing the parameter representation from raw MIMO channel states to effective SINR values that capture the essential detection performance characteristics. This allows AMC decisions to be made based on simplified linear relationships rather than exhaustive non-linear search.
Solution Approach 2:
The patent introduces effective SINR as an intermediary parameter that mediates between the complex MLD process and the AMC decision-making. Instead of directly using MLD outputs or raw channel states, the system computes effective SINR values that serve as a simplified bridge, enabling tractable AMC optimization without requiring full MLD complexity.
2Productivity
If adaptive modulation and coding (AMC) is applied to improve link performance, then data transmission efficiency is improved, but accurate preemptive estimation becomes more difficult due to channel estimation errors
Solution Approach 1:
The patent incorporates feedback mechanisms where the receiver computes effective SINR values based on actual received signals and channel estimates, then feeds back this information to the transmitter for AMC adaptation. This closed-loop feedback enables the system to continuously adjust modulation and coding schemes based on actual channel conditions rather than relying solely on open-loop predictions.
Solution Approach 2:
The patent performs preliminary computation of effective SINR values and AMC parameter selection at the receiver before transmission occurs. By pre-calculating the optimal AMC parameters based on current channel estimates and effective SINR, the system prepares adaptation decisions in advance, reducing the impact of channel estimation errors during actual transmission.
3Device complexity
If linear equalizers are used to simplify MIMO demodulation, then device complexity is reduced, but performance loss occurs compared to optimal MLD
Solution Approach 1:
The patent employs computationally inexpensive linear equalizers and effective SINR calculations as disposable approximations that do not require the heavy computational resources of optimal MLD. These simplified methods are used for AMC decision-making where near-optimal performance is sufficient, and the computational savings enable real-time adaptation without complex processing.
Data Source
AI summary
The present disclosure discloses systems and methods of calculating a near-maximum likelihood detection (MLD) performance capability signal to interference plus noise ratio (SINR) according to instructions stored in non-transitory computer readable memory that when executed by a processor of a multiple-input, multiple output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless communications receiver device cause the processor to perform operations including the processor acquiring Hi and noise variance σn2 for each subcarrier of a set of subcarriers between a MIMO-OFDM wireless communications transmitter device and the wireless communications receiver device, computing an average received bit mutual information rate (RBIR) over all subcarriers, converting the average RBIR to an effective SINR; and selecting a modulation coding scheme (MCS).