Interference Cancellation Receiver Using Segmented Channel Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cellular network interference cancellation techniques are limited by high implementation complexity and sensitivity to interference conditions, particularly in unsynchronized networks, which restricts capacity gains and increases noise levels due to co-channel interference.
Innovation Solution
A method and receiver architecture that separates the estimation of the initial channel impulse response and linear interference cancellation filter coefficients, using known modulation symbols and noise samples to derive coefficients through Least Square or Minimum Mean Square Error solutions, while enabling adaptive filtering and noise characterization to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple receive antennas are used to mitigate co-channel interference through spatial diversity, then interference cancellation performance is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent segments the interference cancellation function into two independent parts: channel estimation and interference cancellation filtering. The channel estimation is performed separately using training symbols, and then the estimated channel response is used to compute interference cancellation filter coefficients. This segmentation allows single-antenna receivers to achieve multi-antenna-like interference cancellation performance without the hardware complexity of multiple antennas.
Solution Approach 2:
The patent replaces the mechanical/spatial approach of using multiple physical antennas with a signal processing approach. Instead of relying on spatial diversity from multiple antennas, the system uses digital signal processing techniques including channel estimation and linear interference cancellation filtering to achieve interference mitigation, thereby substituting physical hardware complexity with computational algorithms.
2Productivity
If joint detection techniques are used to achieve interference cancellation, then capacity gains are improved, but implementation complexity increases
Solution Approach 1:
The patent divides the joint detection process into separate stages: first estimating the channel response using training symbols, then using this estimate to compute interference cancellation filter coefficients. This segmentation simplifies the overall implementation compared to simultaneous joint detection while still achieving capacity gains through effective interference cancellation.
Solution Approach 2:
The patent performs preliminary channel estimation using training symbols before the actual data transmission. This preliminary action allows the system to pre-compute the interference cancellation filter coefficients, which are then applied during data reception. This preliminary estimation approach reduces the complexity of real-time joint detection while maintaining capacity improvement benefits.
3Device complexity
If interference is modeled as noise and simple filtering is applied, then device complexity is reduced, but link-level performance degrades
Solution Approach 1:
The patent employs feedback mechanisms where the estimated channel response is continuously used to update the interference cancellation filter coefficients. The system monitors the received signal, estimates the channel characteristics, and adjusts the filter coefficients accordingly. This feedback loop enables the system to adapt to changing interference conditions while maintaining relatively simple processing architecture.
Solution Approach 2:
The patent changes the parameters of the interference cancellation filter dynamically based on channel conditions. Instead of using fixed filter coefficients, the system estimates channel response parameters and uses these to compute optimal filter coefficients for each transmission instance. This parameter adaptation allows simple filtering architecture to achieve high link-level performance by adjusting filter characteristics to match actual interference conditions.
Data Source
AI summary
A method of receiving a signal formed from information bits propagated through a channel, which has been subjected to interference, the method comprising the steps of: (a) filtering the received signal rn with a linear interference cancellation filter using estimated filter coefficients wn to generate a signal yn; (b) processing the signal yn in a detection unit using an estimated final impulse response of the channel Bn to generate estimates of the transmitted bits; (c) wherein the filter coefficients wn are calculated using the separate steps of: (c1) estimating, using the received signal rn, an initial impulse response cn of the propagation channel; (c2) deriving, using the estimated initial channel impulse response cn and the received signal rn, the filter coefficients wn.