A wireless communication device can expedite beam scans for beam management. The wireless communication device can perform a beam scan using a first beam reference signal of a synchronization signal block (SSB) and a second beam reference signal associated with a physical broadcast control channel (PBCH) of the SSB. For each synchronization signal block (SSB) index (e.g., transmit beam) monitored by the wireless communication device, the wireless communication device can obtain a respective beam quality metric on each of two or more respective receive beams using at least the first and second beam reference signals. Other aspects, features, and embodiments are also claimed and described.

A wireless communication device can expedite beam scans for beam management. The wireless communication device can perform a beam scan using a first beam reference signal of a synchronization signal block (SSB) and a second beam reference signal associated with a physical broadcast control channel (PBCH) of the SSB. For each synchronization signal block (SSB) index (e.g., transmit beam) monitored by the wireless communication device, the wireless communication device can obtain a respective beam quality metric on each of two or more respective receive beams using at least the first and second beam reference signals. Other aspects, features, and embodiments are also claimed and described.

Aspects of the subject disclosure may include, for example, obtaining channel cross correlation data relating to multiple user equipment (UEs) being served in a cell, wherein the channel cross correlation data comprises a correlation coefficient associated with a first UE of the multiple UEs and a second UE of the multiple UEs, identifying that the first UE is experiencing decreasing throughput, responsive to the identifying that the first UE is experiencing decreasing throughput, determining whether the correlation coefficient associated with the first UE and the second UE satisfies a correlation threshold, and, based on a first determination that the correlation coefficient does not satisfy the correlation threshold, adjusting a downlink (DL) transmit power allocation for transmissions directed to the first UE. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, obtaining channel cross correlation data relating to multiple user equipment (UEs) being served in a cell, wherein the channel cross correlation data comprises a correlation coefficient associated with a first UE of the multiple UEs and a second UE of the multiple UEs, identifying that the first UE is experiencing decreasing throughput, responsive to the identifying that the first UE is experiencing decreasing throughput, determining whether the correlation coefficient associated with the first UE and the second UE satisfies a correlation threshold, and, based on a first determination that the correlation coefficient does not satisfy the correlation threshold, adjusting a downlink (DL) transmit power allocation for transmissions directed to the first UE. Other embodiments are disclosed.

A method (100) of route selection in a wireless communication system and a control system (40) is provided. The method includes selecting a route between a first node (1) and a second node (2) and comprises: —evaluating (110) a plurality of possible routes (R1, R2, R3, R4), at least one route (R2, R3, R4) including a third node (3, 4) between the first and the second node; and —selecting (160) the route that has the lowest latency among the possible routes. Especially the method (100) includes: —selecting (120) parameter settings for each link of the possible routes, said selecting (120) comprising; —selecting (130) the length of the cyclic prefix, —evaluating (140) combinations of the selected cyclic prefix and different settings of the at least one further parameter of the physical layer; —selecting (150) the parameter settings that has lowest estimated latency and fulfils at least one communication quality criterion.

A method (100) of route selection in a wireless communication system and a control system (40) is provided. The method includes selecting a route between a first node (1) and a second node (2) and comprises: —evaluating (110) a plurality of possible routes (R1, R2, R3, R4), at least one route (R2, R3, R4) including a third node (3, 4) between the first and the second node; and —selecting (160) the route that has the lowest latency among the possible routes. Especially the method (100) includes: —selecting (120) parameter settings for each link of the possible routes, said selecting (120) comprising; —selecting (130) the length of the cyclic prefix, —evaluating (140) combinations of the selected cyclic prefix and different settings of the at least one further parameter of the physical layer; —selecting (150) the parameter settings that has lowest estimated latency and fulfils at least one communication quality criterion.

The disclosure provides a wireless channel scenario identification method and system. The method includes: simulating different wireless channel scenarios to obtain a channel scenario baseband signal y(t).sub.pq; extracting a feature parameter of y(t).sub.pq, extracting an autocorrelation function A.sub.h(t).sub.pq and performing a Fourier transform thereon to obtain a power spectral density function S(t).sub.pq; normalizing S(t).sub.pq to obtain a normalized channel scenario power spectral density function S(t).sub.pq; designing a deep learning network and inputting S(t).sub.pq and a category label pair to train the deep learning network; and for a system with a channel scenario to be identified, collecting a passband signal at its receiving end, obtaining the normalized scenario power spectral density function Ŝ(t).sub.pq, and using Ŝ(t).sub.pq as an input of the trained classifier, the output of the classifier being a label sequence of the channel scenario, and the channel scenario is effectively determined.

The disclosure provides a wireless channel scenario identification method and system. The method includes: simulating different wireless channel scenarios to obtain a channel scenario baseband signal y(t).sub.pq; extracting a feature parameter of y(t).sub.pq, extracting an autocorrelation function A.sub.h(t).sub.pq and performing a Fourier transform thereon to obtain a power spectral density function S(t).sub.pq; normalizing S(t).sub.pq to obtain a normalized channel scenario power spectral density function S(t).sub.pq; designing a deep learning network and inputting S(t).sub.pq and a category label pair to train the deep learning network; and for a system with a channel scenario to be identified, collecting a passband signal at its receiving end, obtaining the normalized scenario power spectral density function Ŝ(t).sub.pq, and using Ŝ(t).sub.pq as an input of the trained classifier, the output of the classifier being a label sequence of the channel scenario, and the channel scenario is effectively determined.

Methods for configuring an optical link in which a distribution of transmission data rates and line rates are configured for a predetermined amount of optical bandwidth to maximize transmission capacity. In these methods, a controller of an optical network obtains input parameters that include a signal-to-noise ratio (SNR) for optical signals and an allocated bandwidth of the optical link, further obtains, for each line rate, a mapping of transmission data rates along a frequency spectrum of the allocated bandwidth compatible with the SNR, and generates a channel plan in which a number of traffic modes and a distribution of a plurality of channels in the allocated bandwidth are set to maximize transmission capacity. The plurality of channels is used for transmitting the signals on the optical link. The controller configures at least one optical network element in the optical network to establish the optical link based on the channel plan.

Methods for configuring an optical link in which a distribution of transmission data rates and line rates are configured for a predetermined amount of optical bandwidth to maximize transmission capacity. In these methods, a controller of an optical network obtains input parameters that include a signal-to-noise ratio (SNR) for optical signals and an allocated bandwidth of the optical link, further obtains, for each line rate, a mapping of transmission data rates along a frequency spectrum of the allocated bandwidth compatible with the SNR, and generates a channel plan in which a number of traffic modes and a distribution of a plurality of channels in the allocated bandwidth are set to maximize transmission capacity. The plurality of channels is used for transmitting the signals on the optical link. The controller configures at least one optical network element in the optical network to establish the optical link based on the channel plan.