MIMO Codebook Power Weighting for Successive Cancellation
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Solution Overview
Problem
Existing limited feedback methods for Multiple Input Multiple Output (MIMO) transmission are not optimized for successive cancellation receivers, particularly in broadband communication systems, and do not effectively handle scenarios with more transmit antennas than MIMO streams.
Innovation Solution
The method involves determining codebook weights and power weightings for each MIMO data stream over a group of frequency-domain subcarriers, with antenna selection and power weighting strategies to improve successive cancellation performance, using a codebook that includes zero entries for unselected antennas, and feeding back these weights for optimized beamforming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If limited feedback methods are used to reduce feedback overhead, then feedback quantity is reduced, but receiver performance is not optimized for successive cancellation
Solution Approach 1:
The patent changes the parameters of the feedback information by introducing power weightings and selective channel quality indicator (CQI) feedback instead of full channel state information. This reduces feedback overhead while providing sufficient information for successive cancellation receivers to achieve near-optimal performance by adjusting power allocation and selecting representative CQI values across frequency subcarriers.
Solution Approach 2:
The patent performs preliminary optimization at the receiver side by calculating power weightings and selecting codebook indices before feedback transmission. The receiver pre-processes the channel state information to extract only the essential parameters needed for MIMO transmission, thereby reducing feedback overhead while maintaining performance through advance computation of optimal power allocations and beamforming weights.
2Device complexity
If codebook-based beamforming is used with antenna selection, then implementation complexity is reduced, but performance is not optimized for successive cancellation receivers
Solution Approach 1:
The patent enhances codebook-based beamforming by introducing power weighting parameters and optimized CQI selection specifically tailored for successive cancellation receivers. Instead of using uniform power allocation across antennas, the system calculates and feeds back power weightings that optimize the performance of successive cancellation, thereby maintaining low implementation complexity while significantly improving receiver performance.
Solution Approach 2:
The patent segments the feedback information into distinct components: codebook indices for beamforming direction, power weightings for each transmit antenna, and selective CQI values. This segmentation allows the system to maintain the simplicity of codebook-based approaches while adding targeted optimizations for successive cancellation receivers through separate power weighting parameters that can be independently computed and applied.
3Reliability
If full broadband channel knowledge is obtained at transmitter, then MIMO transmission performance is maximized, but feedback overhead increases significantly
Solution Approach 1:
The patent transforms the feedback from full channel state information to a compressed representation consisting of power weightings, codebook indices, and selective CQI values. This parameter transformation maintains the essential information needed for high-performance MIMO transmission with successive cancellation receivers while reducing feedback overhead by exploiting the structure and correlations in the channel state information across frequency and space.
Solution Approach 2:
The patent performs preliminary processing of channel state information at the receiver before feedback transmission. The receiver pre-calculates power weightings, selects representative CQI values, and determines optimal codebook indices in advance, thereby compressing the channel knowledge into essential parameters that can be fed back with minimal overhead while preserving the information needed for optimized MIMO transmission.
Data Source
AI summary
A method for communicating a plurality of data streams between a transmitting device with multiple transmit antennas and a receiving device, is disclosed. The method comprises determining a list consisting of a subset of the multiple transmit antennas on which the transmitting device will transmit data, determining a set of power weightings, providing the set of power weightings and the list of the subset of the multiple transmit antennas to the transmitting device, weighting a plurality of data streams by the power weightings, and transmitting the power weighted data streams on the subset of the multiple transmit antennas to the receiving device. Another aspect of the invention comprises maintaining a codebook consisting of a plurality of transmit weight vectors at both the transmitting device and the receiving device. The method also comprises determining a list consisting of a subset of the plurality of transmit weight vectors which to use for transmitting the multiple data streams, determining a set of power weightings to be use for each data stream, providing the set of power weightings and the list of the subset of the plurality of transmit weight vectors to the transmitting device, and weighting the data streams by the power weightings and beamforming the data streams with the subset of the plurality of transmit weight vectors.