Abstract: A communication circuit supports a first communication protocol and a second communication protocol that is different from the first communication protocol. A number of signals include first signals conveying first information messages and second signals conveying second information messages. The first information messages include a repetitive message having fixed repeated content and the second information messages include a non-repetitive message having variable content. The first signals and the second signals are transmitted via the communication circuit using the first communication protocol for the first signals and the second communication protocol for the second signals.

Abstract: A communication circuit supports a first communication protocol and a second communication protocol that is different from the first communication protocol. A number of signals include first signals conveying first information messages and second signals conveying second information messages. The first information messages include a repetitive message having fixed repeated content and the second information messages include a non-repetitive message having variable content. The first signals and the second signals are transmitted via the communication circuit using the first communication protocol for the first signals and the second communication protocol for the second signals.

Abstract: A communication circuit supports a first communication protocol and a second communication protocol that is different from the first communication protocol. A number of signals include first signals conveying first information messages and second signals conveying second information messages. The first information messages include a repetitive message having fixed repeated content and the second information messages include a non-repetitive message having variable content. The first signals and the second signals are transmitted via the communication circuit using the first communication protocol for the first signals and the second communication protocol for the second signals.

Abstract: A communication circuit supports a first communication protocol and a second communication protocol that is different from the first communication protocol. A number of signals include first signals conveying first information messages and second signals conveying second information messages. The first information messages include a repetitive message having fixed repeated content and the second information messages include a non-repetitive message having variable content. The first signals and the second signals are transmitted via the communication circuit using the first communication protocol for the first signals and the second communication protocol for the second signals.

Abstract: A semiconductor device, for example an integrated circuit such as a microcontroller (MCU) or a digital signal processor (DSP), includes a semiconductor die coupled with a power supply line, a debug module coupled with the semiconductor die to exchange semiconductor die debug command and data signals with the semiconductor die, and a modem coupled with the power supply line. The debug module is arranged to convey the semiconductor die debug command and data signals over the power supply line.

Abstract: A semiconductor device, for example an integrated circuit such as a microcontroller (MCU) or a digital signal processor (DSP), includes a semiconductor die coupled with a power supply line, a debug module coupled with the semiconductor die to exchange semiconductor die debug command and data signals with the semiconductor die, and a modem coupled with the power supply line. The debug module is arranged to convey the semiconductor die debug command and data signals over the power supply line.

Abstract: Digital data signals such as, e.g., turbo-encoded data signals subject to decoding, are processed by producing a plurality of families of metrics for these signals while allowing one or more of these metrics to wrap through a respective independent wrapping operation. A decoder, e.g., a decoder for turbo-encoded digital signals computes differences of metrics selected out of the plurality of families of metrics by excluding differences of metrics derived through independent wrapping operations (e.g., wrapping metrics from different families) and generates signals representative of order relationships of combinations of corresponding unwrapped metrics as a function of said differences.

Abstract: Digital data signals such as, e.g., turbo-encoded data signals subject to decoding, are processed by producing a plurality of families of metrics for these signals while allowing one or more of these metrics to wrap through a respective independent wrapping operation. A decoder, e.g., a decoder for turbo-encoded digital signals computes differences of metrics selected out of the plurality of families of metrics by excluding differences of metrics derived through independent wrapping operations (e.g., wrapping metrics from different families) and generates signals representative of order relationships of combinations of corresponding unwrapped metrics as a function of said differences.

Abstract: The method transmits a long packet of digital data over a poly-phase power line affected by impulsive noise synchronous with phase voltages. Instead of using very complicated coding schemes, starting from the knowledge of the typical power line scenario, useful information is transmitted where noise synchronous with the main signal is absent. Time-intervals of a known or estimated duration during which the poly-phase power line is affected by impulsive noise are determined, and dummy data during the time-intervals, and useful data during other time-intervals free from impulsive noise, are transmitted.

Abstract: The recognition of a frame synchronization pattern or unique word of a received signal may be enhanced using a data-aided estimator of the signal-to-noise ratio (SNR) together with a correlation detector of the unique word to be received. Detecting a frame synchronization pattern or a unique word in a received signal, the SNR is estimated on the received signal with a data-aided SNR estimator using the unique word to be received. If the estimated SNR exceeds a certain threshold, an eventual recognition of the unique word established by a correlation correlator of the receiver is considered reliable. Comparing the SNR with the threshold may be carried out either before or after the correlator has processed the unique word.

Abstract: A method of estimating log-likelihood ratios for first and second streams of samples of a received S-FSK signal demodulated using first and second carriers includes estimating channel and noise parameters associated with first and second transmitted values for the first and second streams of samples obtained from the received S-FSK modulated signal. Current signal-to-noise ratios are estimated for current samples of the first and second streams of samples obtained from the received S-FSK modulated signal using the channel and noise parameters. The estimated current signal-to-noise ratios are compared with values of a discrete ordered set and respective pairs of consecutive values of the discrete ordered set between which the estimated current signal-to-noise ratios are comprised are identified. Log-likelihood ratios are estimated for the current samples of the first and second streams.

Abstract: A method for loading bits over a set of subcarriers of a multiple-carrier communications system comprises the operation of associating with the subcarriers respective numbers of bits chosen from among a plurality of available constellations. The method envisages definition of a performance target for the system and execution of bit loading, guaranteeing the aforesaid target on a plurality of subcarriers. The performance target can be a target error rate, such as a bit-error rate (BER), or else be transferred into a constraint, such as, for example, a threshold, in a metric of log-likelihood ratios (LLRs). In this case, there is preferably envisaged application to the signals received within the multiple-carrier system a function that estimates a signal to noise ratio on each sub-carrier. The aforesaid metric of log-likelihood ratios (LLRs) is hence defined as a function of said signal to noise ratios.

Abstract: Log-likelihood ratios are approximated for encoded bits modulated with a 2m-ary QAM constellation. Each symbol of the constellation is identified by a respective string of m bits. The log-likelihood ratio of each bit of the m bits is approximated with a product ? of a respective factor by a respective variable D that depends on a received signal and on communication channel characteristics. The approximating includes determining a value of at least one of the variables D using a parametric nonlinear function of an equalized replica z of a respective received signal.

Abstract: A method of estimating log-likelihood ratios for first and second streams of samples of a received S-FSK signal demodulated using first and second carriers includes estimating channel and noise parameters associated with first and second transmitted values for the first and second streams of samples obtained from the received S-FSK modulated signal. Current signal-to-noise ratios are estimated for current samples of the first and second streams of samples obtained from the received S-FSK modulated signal using the channel and noise parameters. The estimated current signal-to-noise ratios are compared with values of a discrete ordered set and respective pairs of consecutive values of the discrete ordered set between which the estimated current signal-to-noise ratios are comprised are identified. Log-likelihood ratios are estimated for the current samples of the first and second streams.

Abstract: The recognition of a frame synchronization pattern or unique word of a received signal may be enhanced using a data-aided estimator of the signal-to-noise ratio (SNR) together with a correlation detector of the unique word to be received. Detecting a frame synchronization pattern or a unique word in a received signal, the SNR is estimated on the received signal with a data-aided SNR estimator using the unique word to be received. If the estimated SNR exceeds a certain threshold, an eventual recognition of the unique word established by a correlation correlator of the receiver is considered reliable. Comparing the SNR with the threshold may be carried out either before or after the correlator has processed the unique word.

Abstract: The method transmits a long packet of digital data over a poly-phase power line affected by impulsive noise synchronous with phase voltages. Instead of using very complicated coding schemes, starting from the knowledge of the typical power line scenario, useful information is transmitted where noise synchronous with the main signal is absent. Time-intervals of a known or estimated duration during which the poly-phase power line is affected by impulsive noise are determined, and dummy data during the time-intervals, and useful data during other time-intervals free from impulsive noise, are transmitted.

Abstract: A method for loading bits over a set of subcarriers of a multiple-carrier communications system comprises the operation of associating with the subcarriers respective numbers of bits chosen from among a plurality of available constellations. The method envisages definition of a performance target for the system and execution of bit loading, guaranteeing the aforesaid target on a plurality of subcarriers. The performance target can be a target error rate, such as a bit-error rate (BER), or else be transferred into a constraint, such as, for example, a threshold, in a metric of log-likelihood ratios (LLRs). In this case, there is preferably envisaged application to the signals received within the multiple-carrier system a function that estimates a signal to noise ratio on each sub-carrier. The aforesaid metric of log-likelihood ratios (LLRs) is hence defined as a function of said signal to noise ratios.

Abstract: Log-likelihood ratios are approximated for encoded bits modulated with a 2m-ary QAM constellation. Each symbol of the constellation is identified by a respective string of m bits. The log-likelihood ratio of each bit of the m bits is approximated with a product ? of a respective factor by a respective variable D that depends on a received signal and on communication channel characteristics. The approximating includes determining a value of at least one of the variables D using a parametric nonlinear function of an equalized replica ? of a respective received signal.