A disclosed computer-implemented method may include receiving, as part of a demodulation reference signal (DMRS) channel estimation operation, a frequency domain channel estimation signal comprising a plurality of DMRS samples, and generating an extended channel estimation signal by: (A) determining an extended DMRS sample that extends at least one edge of the channel estimation signal based on: (i) an edge DMRS sample included in the plurality of DMRS samples at the edge of the channel estimation signal, and (ii) at least one additional DMRS sample included in the plurality of DMRS samples, and (B) extending the edge of the channel estimation signal by including the DMRS samples and the extended DMRS sample in the extended channel estimation signal. The method may also include generating an augmented channel estimation signal by extrapolating a frequency edge for the augmented channel estimation signal. Various other systems and methods are also disclosed.

A receiver performing a half cyclic prefix (CP) shift on received subframes is disclosed, comprising: an analog to digital conversion (ADC) module; a cyclic prefix (CP) removal module coupled to the ADC module configured to retain a portion of cyclic prefix samples; a fast Fourier transform (FFT) module configured to receive samples from the cyclic prefix removal module, and to perform a FFT procedure on the received samples using a FFT window, the FFT window being shifted ahead based on the retained portion of cyclic prefix samples, to output an orthogonal frequency division multiplexed (OFDM) symbol; and a rotation compensation module coupled to the FFT module, the rotation compensation module configured to perform phase de-rotation of the OFDM symbol.

Highly efficient digital domain sub-band based receivers and transmitters.

Provided are a preamble symbol generation method and receiving method, and a relevant frequency-domain symbol generation method and a relevant device, characterized in that the method comprises: generating a prefix according to a partial time-domain main body signal truncated from a time-domain main body signal; generating the hyper prefix according to the entirety or a portion of the partial time-domain main body signal; and generating time-domain symbol based on at least one of the cyclic prefix, the time-domain main body signal and the hyper prefix, the preamble symbol containing at least one of the time-domain symbols.

A broadcast signal receiver includes a tuner for tuning a broadcast signal, a reference signal detector for detecting pilots from the tuned broadcast signal, a de-framer for de-framing a signal frame of the broadcast signal and deriving service data based on a number of carriers of the signal frame, and a decoder for performing error correction process on the derived service data.

Disclosed are techniques related to wireless communication. In an aspect, a sequence generating entity factorizes a comb size N into prime factors of N, and generates one or more offset sequences for a reference signal for positioning based on one or more sequence lists associated with the prime factors of N and a number of symbols M over which the reference signal is scheduled.

Methods and an apparatus are provided. A first method includes receiving an estimated first arrival path (FAP); processing the estimated FAP; providing a rounding operation on the processed estimated FAP to generate an adjustment value for adjusting a fast Fourier transform (FFT) window; determining a quantization error based on the processed estimated FAP; and summing the quantization error to the processed estimated FAR A second method includes receiving an estimated FAP; determining a weighted average of the estimated FAP; processing the weighted average of the estimated FAP; providing a rounding operation on the processed weighted average of the estimated FAP to generate an adjustment value for adjusting an FFT window; determining a delayed STR adjustment based on the processed weighted average of the estimated FAP in a previous time slot; and summing the delayed STR adjustment to the processed weighted average of the estimated FAP in a current time slot.

Some examples of handling FTM requests comprises receiving a plurality of fine timing measurement (FTM) requests from a second network device over a first channel. Determining a channel traffic along the first channel. Adjusting a FTM response frequency based on the channel traffic. Responding based on the FTM response frequency, to a first number of FTM requests out of the plurality of FTM requests.

According to one embodiment, a distance technique between a transmitter and a receiver for processing a signal in symbol units is presented. According to the embodiment, the transmitter transmits a transmission signal to the receiver through preset first and second frequencies. Then, the transmitter receives, from the receiver, a reception signal corresponding to the transmission signal. The reception signal includes a first reception component corresponding to the first frequency and a second reception component corresponding to the second frequency. The phase difference set by the receiver is applied between the phase of the first reception component and the phase of the second reception component. The phase difference is set on the basis of the difference between a reception time at which the transmission signal is received by the receiver and a processing time at which the transmission signal is processed in the receiver.

Monitoring an operational characteristic of a data communication device within a network includes sampling an operational characteristic of the data communication device at a fine-grain sample rate over a first sampling interval to produce fine-grain samples of the operational characteristic of the data communication device, training a machine learning algorithm using the fine-grain samples of the operational characteristic of the data communication device, the fine-grain sample rate, and a coarse-grain sample rate that is less than the fine-grain sample rate, sampling the operational characteristic of the data communication device at the coarse-grain sample rate over a second sampling interval to produce coarse-grain samples of the operational characteristic of the data communication device, and using the machine learning algorithm to process the coarse-grain samples of the operational characteristic of the data communication device to produce accuracy-enhanced samples of the operational characteristic of the data communication device.