Abstract: Techniques for scaling symbols to account for large abrupt changes in received power at a user equipment (UE) are described. The UE performs AGC on received samples to obtain input samples. The UE processes (e.g., CDMA demodulates) the input samples to obtain first symbols. The UE determines the power of the input samples and derives a symbol gain based on (e.g., inversely related to) the power of the input samples. The UE scales the first symbols with the symbol gain to obtain detected data symbols having approximately constant amplitude, even with large abrupt changes in the power of the input samples. The UE estimates signal amplitude and noise variance based on the detected data symbols, computes LLRs for code bits of the detected data symbols based on the signal amplitude and noise variance, and decodes the LLRs to obtain decoded data.

Abstract: Techniques for efficiently and accurately computing log-likelihood ratio (LLRs) for code bits are described. A set of code bits may be mapped to a modulation symbol in a signal constellation. Different code bits in the set may be associated with different LLR functions. A receiver obtains received symbols for a transmission sent via a communication channel. The receiver derives LLRs for code bits based on the received symbols and piecewise linear approximation of at least one LLR function. The piecewise linear approximation of each LLR function may comprise one or more linear functions for one or more ranges of input values. The receiver may select one of the linear functions for each code bit based on a corresponding received symbol component value. The receiver may then derive an LLR for each code bit based on the linear function selected for that first code bit.