Abstract:
Aspects for machine learning-based link adaptation are described. For example, an apparatus can determine k-nearest neighbors (K-NNs) based on training data associated with the sub-band and on the signal to interference and noise ratio (SINR) of the sub-band. In aspects, the apparatus can identify a channel quality indicator (CQI) associated with the lowest error rate for the k-NNs and provide the identified CQI to a base station. In aspects, a neural network (NN) can provide labels for CQIs that indicate probability of choosing a CQI, and the CQI having highest probability will be provided to a base station. In aspects, a covariance matrix based on samples of a communication channel can be provided to a NN to determine a rank indicator (RI) corresponding to the channel, and channel state information associated with the (RI) can be sent to the base station. Other aspects are described.
Abstract:
Embodiments of the present invention provide a virtual multicarrier design for orthogonal frequency division multiple access communications. Other embodiments may be described and claimed.
Abstract:
Embodiments of the present invention provide a virtual multicarrier design for orthogonal frequency division multiple access communications. Other embodiments may be described and claimed.
Abstract:
Embodiments of the present invention provide a virtual multicarrier design for orthogonal frequency division multiple access communications. Other embodiments may be described and claimed.
Abstract:
A user equipment comprises one or more antennas, a processor to communicate with an enhanced Node B (eNB) of an Internet Protocol (IP) based wireless communication network via the antenna; and a storage medium coupled to the processor, the storage medium having instructions stored thereon, that if executed by the processor, result in: requesting the eNB for a direct communication with a second user equipment, wherein the user equipment and the second user equipment are in a cell of the eNB; performing a first channel measurement based on a command from the eNB; receiving direct communication related information from the eNB based on a result of the first channel measurement; and performing a configuration based on the direct communication related information to perform the direct communicate with the second user equipment.
Abstract:
Embodiments of the present invention provide a virtual multicarrier design for orthogonal frequency division multiple access communications. Other embodiments may be described and claimed.
Abstract:
Embodiments of user equipment and methods for improved uplink transmission power management and scheduling, are generally described herein. For example, in an aspect, a method of uplink power management is presented, the method includes determining whether a total desired transmission power exceeds a total configured maximum output power for a subframe. When the total desired transmission power exceeds the total configured maximum output power, the method includes allocating a minimum proactive power limitation to each serving cell, assigning a remaining power to one or more channels based on priority, and computing a total power assignment based on the allocating and the assigning.
Abstract:
Channel quality information feedback techniques for a wireless system are described. An apparatus may comprise a base station having base station logic to determine a channel quality indicator feedback dimension value representing a number of resource blocks for an orthogonal frequency division multiple access system to be measured by a subscriber station based on a matching ratio value, and a transceiver to send the channel quality indicator feedback dimension value to the subscriber station. Other embodiments are described and claimed.
Abstract:
An apparatus and method that allow user equipment (UE) to transmit information directly with other user equipment, using a device-to-device (D2D) mode is disclosed herein. A first D2D UE (dUE1) that wishes so communicate to a second D2D UE (dUE2) in D2D mode makes various communications requests to an Evolved Node B (eNB), which can facilitate the connection between the dUE1 and the dUE2. Among these requests are to make the D2D connection via WiFi instead of via Long Term Evolution (LTE). The eNB determines the WiFi capabilities of dUE1 and dUE2, then assigns a subset of available channels to be scanned by dUE1 and a separate subset of available channels to be scanned by dUE2. Thereafter, the eNB can assign a WiFi channel based on the scans performed by dUE1 and dUE2.
Abstract:
Aspects for machine learning-based link adaptation are described. For example, an apparatus can determine k-nearest neighbors (K-NNs) based on training data associated with the sub-band and on the signal to interference and noise ratio (SINR) of the sub-band. In aspects, the apparatus can identify a channel quality indicator (CQI) associated with the lowest error rate for the k-NNs and provide the identified CQI to a base station. In aspects, a neural network (NN) can provide labels for CQIs that indicate probability of choosing a CQI, and the CQI having highest probability will be provided to a base station. In aspects, a covariance matrix based on samples of a communication channel can be provided to a NN to determine a rank indicator (RI) corresponding to the channel, and channel state information associated with the (RI) can be sent to the base station. Other aspects are described.