Wireless Reference Signal Sequence Generation for MIMO Systems
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Solution Overview
Problem
Current reference signal designs for wireless communication systems, particularly in MIMO systems, face challenges in minimizing cross-correlation and optimizing resource allocation, leading to increased storage requirements and interference issues due to variable correlation properties and stringent time and frequency resource constraints.
Innovation Solution
The method involves designing reference signals using alternating projections to achieve sequences with minimum average cross-correlation, employing Zadoff-Chu sequences and cyclic shifts, and utilizing multiple bandwidth allocations to ensure orthogonality and minimal Peak to Average Power Ratio, while recursively generating sequences from a base sequence to meet design considerations such as Welch Bound and cyclic prefix requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If reference signals are designed without minimum cross-correlation constraints, then sequence generation is simpler, but storage requirements increase
Solution Approach 1:
The reference signal design is segmented into multiple sequences with different cross-correlation properties. By dividing the reference signal space into segments with controlled cross-correlation, the system achieves both manageable storage requirements and simplified generation processes for each segment.
Solution Approach 2:
The patent applies parameter changes by transforming reference sequences through operations such as cyclic shifts, conjugation, and multiplication by Zadoff-Chu sequences. These parameter transformations generate diverse reference signals from a limited set of base sequences, reducing storage requirements while maintaining generation simplicity.
2Ease of manufacture
If cross-correlation between reference signals is not minimized, then sequence design is easier, but interference issues increase
Solution Approach 1:
The patent systematically changes sequence parameters including cyclic shifts, conjugation, and Zadoff-Chu sequence multiplication to minimize cross-correlation. These parameter transformations maintain design ease while effectively reducing interference between reference signals from different mobile stations.
Solution Approach 2:
The patent converts the potentially harmful effect of sequence repetition and reuse into a benefit by deliberately designing sequences with controlled cross-correlation properties. By using mathematical transformations on reused sequences, the system maintains generation simplicity while turning potential interference into orthogonal or near-orthogonal signal relationships.
3Reliability
If more reference signals are allocated to mobile stations, then demodulation performance improves, but time and frequency resource constraints become more stringent
Solution Approach 1:
The patent creates a universal reference signal framework where a limited set of base sequences can serve multiple mobile stations through systematic transformations. This multi-functionality allows the same base sequences to be reused across different mobile stations and resource allocations, improving demodulation performance without proportionally increasing resource consumption.
Solution Approach 2:
The patent performs preliminary actions by pre-defining a compact set of base sequences with optimized cross-correlation properties. These pre-designed sequences are then transformed through cyclic shifts and other operations to generate the full set of reference signals needed, allowing efficient resource allocation while maintaining high demodulation performance.
4Quantity of substance
If reference signals are optimized for re-use, then storage requirements decrease, but cross-correlation properties become variable
Solution Approach 1:
The patent systematically applies parameter changes through mathematical transformations (cyclic shifts, conjugation, Zadoff-Chu multiplication) that preserve controlled cross-correlation properties even as sequences are reused. These transformations ensure that while storage requirements decrease through re-use, the cross-correlation stability is maintained through structured parameter modifications.
Data Source
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AI summary
A method for generating sequences that are nearest to a set of sequences with minimum average cross-correlation is described. Each element of a set of sequences is projected to a nearest constellation point. The set of sequences is converted into a time domain representation. An inverse discrete Fourier Transform (IDFT) is performed on the set of sequences. A cubic metric of each sequence of the set of sequences is evaluated. A sequence is removed from the set if the cubic metric exceeds a threshold. A minimum maximum cross-correlation is obtained for the set of sequences.