CAZAC Sequence Generation for Low-Autocorrelation Wireless Synchronization
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Solution Overview
Problem
Conventional methods fail to generate sequences with sufficient low autocorrelation properties for fourth-generation mobile communications, particularly for channel estimation and synchronization in cellular networks.
Innovation Solution
A complex-valued constant amplitude zero cyclic autocorrelation (CAZAC) sequence is generated using the Zadoff-Chu sequence formula, with iterative calculations and symmetry properties to reduce error propagation and processor power consumption, allowing for efficient channel estimation and synchronization in wireless communication networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional sequence generation approaches are used, then the implementation is simple, but the autocorrelation properties are insufficient for fourth-generation mobile communications
Solution Approach 1:
The patent segments the sequence generation process into iterative calculations where the CAZAC sequence is generated step-by-step through multiple iterations. Each iteration computes a portion of the sequence using the formula x[n] = exp(j*2*π*u*n^2/N), allowing the complex generation process to be broken down into manageable computational steps that achieve low autocorrelation properties.
Solution Approach 2:
The patent applies preliminary action by pre-calculating and storing values in lookup tables before the actual sequence generation. The autocorrelation values and sequence elements are computed in advance and stored, so that during runtime, the system can quickly retrieve pre-computed values rather than performing complex calculations in real-time, thus achieving low autocorrelation properties efficiently.
2Reliability
If iterative calculations are performed to generate CAZAC sequences, then the autocorrelation property improves, but the processor power consumption increases
Solution Approach 1:
The patent significantly reduces processor power consumption by performing preliminary calculations and storing results in lookup tables. The system pre-computes CAZAC sequence elements and their autocorrelation properties, then stores these values for rapid retrieval during channel estimation and synchronization operations. This eliminates the need for repeated complex iterative calculations during runtime.
Solution Approach 2:
The patent uses copying by creating and storing copies of pre-computed CAZAC sequence values in lookup tables. Instead of recalculating sequences repeatedly, the system copies and retrieves stored sequence elements, which dramatically reduces the computational energy required during actual communication operations while maintaining the low autocorrelation properties needed for accurate channel estimation.
3Measurement precision
If the sequence length is increased to improve channel estimation, then the error propagation increases
Solution Approach 1:
The patent applies feedback by using the known structure and properties of CAZAC sequences to verify and correct calculations during the generation process. The system leverages the inherent zero-autocorrelation property of CAZAC sequences as a feedback mechanism to detect and correct errors, ensuring that even as sequence length increases for better channel estimation precision, error propagation is controlled through the mathematical properties of the sequence itself.
Data Source
AI summary
A method, system and apparatus for generating a constant amplitude zero autocorrelation (CAZAC) sequence to be transmitted on a wireless communication channel between a user equipment and a base station within a cellular communication network includes iteratively calculating elements of the CAZAC sequence according to a CAZAC sequence formula until a number of iterations has reached a predetermined iteration value determined in accordance with a number of subcarriers associated with the channel; obtaining a value of particular elements of the CAZAC sequence from a table of stored values at predetermined reset iteration values in order to limit error propagation; and generating the reference signal based upon the elements of the CAZAC sequence. The CAZAC sequence formula is one of a Chu sequence, Frank-Zadoff sequence, Zadoff-Chu (ZC) sequence, and Generalized Chirp-Like (GCL) Sequence.