Coefficients for Global Minimax Approximations and Bounds for the Gaussian Q-Function

A 2020 supplementary dataset for a paper published in IEEE Transactions on Communications. It contains sets of optimized coefficients for novel minimax approximations and bounds of the Gaussian Q-function, its integer powers, and a related average symbol error probability case. The dataset was authored by Islam M. Tanash of Tampere University.

Use Cases

• Implementing efficient approximations for the Gaussian Q-function based on the provided coefficient sets.
• Analyzing relative error bounds in communication system models using the described exponential sum form.
• Calculating average symbol error probability for 4-QAM detection scenarios as described in the paper.
• Benchmarking new approximation methods against the published global minimax coefficients.

Strengths

• Coefficients are provided for up to twenty-five exponential terms, offering a range of approximation complexities.
• The right boundary parameter (x_K+1) ranges from 1 to 10 in steps of 0.1, allowing for fine-grained error analysis.
• Includes coefficients for the Gaussian Q-function, its first four integer powers, and a specific polynomial case for 4-QAM detection.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and dataset size are unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Supplementary material for the paper by I. M. Tanash and T. Riihonen in IEEE Transactions on Communications, vol. 68, no. 10, Oct. 2020.

Collection Method

Coefficients were likely generated through numerical optimization as part of the research methodology.

Time Range

2020

Freshness

Unknown

Geography

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