Abstract:
Apparatus and methods include receiving one or more first signals at a user equipment (UE) during a first portion of a transmission time interval (TTI), wherein the one or more first signals are transmitted by a network to the UE using a transport format; determining the transport format upon receiving the one or more first signals and prior to a second portion of the TTI subsequent to the first portion of the TTI; and receiving one or more second signals at the UE during a second portion of the TTI.
Abstract:
Apparatus and methods include receiving one or more first signals at a user equipment (UE) during a first portion of a transmission time interval (TTI), wherein the one or more first signals are transmitted by a network to the UE using a transport format; determining the transport format upon receiving the one or more first signals and prior to a second portion of the TTI subsequent to the first portion of the TTI; and receiving one or more second signals at the UE during a second portion of the TTI.
Abstract:
Access terminals are adapted to facilitate estimation of signal-to-noise ratios for received wireless transmissions. According to at least one example, a wireless communication device can receive a plurality of data symbols. The wireless communication device can determine a first estimate of a signal-to-noise ratio based on first estimates of a signal power and a noise power associated with the plurality of received data symbols. When the first estimate of the signal-to-noise ratio is below a predetermined threshold, a second estimate of the signal-to-noise ratio can be determined based on second estimates of the signal power and the noise power for the received data symbols. Other aspects, embodiments, and features are also included.
Abstract:
A reliability metric is used for determining whether to prune a decoding hypothesis. For example, a reliability metric can be generated for each possible hypothesis generated during blind decoding operations. The reliability metric can then be used in a pruning process whereby a determination to prune a given hypothesis is based on whether the corresponding reliability metric is above or below a reliability metric threshold. In some aspects, the reliability metric is based on the correlation between the symbols of a hypothesis and re-encoded symbols that are based on the hypothesis, whereby the correlation is normalized using an estimated power parameter that is independent of the hypothesis. Through the use of the reliability metric, decoding may be achieved with a low probability of false passes (in the case of noise) and a low probability of missed detection (in the case of a real signal).
Abstract:
Methods and apparatus for improving amplitude estimation of a received signal in a wireless communication system is provided. Aspects of the methods and apparatus relate to investigating estimation of signal-to-noise (SNR) of the signal. To estimate SNR of the signal, a user equipment (UE) combines previous pilot amplitude measurements and the present pilot amplitude measurement along with received transmit power control (TPC) commands.
Abstract:
The present disclosure presents a method and an apparatus for reducing cyclic redundancy check (CRC) false detections at a user equipment (UE). For example, the method may include receiving a data packet at the UE, determining whether a state metric value for each of a plurality of vector elements of a last path metric vector of the data packet is less than or equal to a first threshold, incrementing a counter when the state metric value of a vector element of the plurality of vector elements is less than or equal to the first threshold, determining whether the counter is lower than a second threshold, and providing the data packet to an upper layer protocol entity of the UE when a CRC pass for the data packet is determined and the counter is lower than the second threshold. As such, reduced CRC false detections at a UE may be achieved.
Abstract:
A reliability metric is used for determining whether to prune a decoding hypothesis. For example, a reliability metric can be generated for each possible hypothesis generated during blind decoding operations. The reliability metric can then be used in a pruning process whereby a determination to prune a given hypothesis is based on whether the corresponding reliability metric is above or below a reliability metric threshold. In some aspects, the reliability metric is based on the correlation between the symbols of a hypothesis and re-encoded symbols that are based on the hypothesis, whereby the correlation is normalized using an estimated power parameter that is independent of the hypothesis. Through the use of the reliability metric, decoding may be achieved with a low probability of false passes (in the case of noise) and a low probability of missed detection (in the case of a real signal).
Abstract:
A signal-to-interference target is adjusted multiple times within a transmission time interval. For example, the signal-to-interference target may be adjusted at the slot level. According to some aspects of the disclosure, the signal-to-interference target may be adjusted based on early detection of the transport format being transmitted by the network. For example, the signal-to-interference target may be quickly adjusted at each slot upon detection of the kind of transport format present during that slot. Advantageously, such an approach may reduce the transient time that it takes for the signal-to-interference target to be updated to a new transport format.
Abstract:
Access terminals are adapted to facilitate estimation of signal-to-noise ratios for received wireless transmissions. According to at least one example, a wireless communication device can receive a plurality of data symbols. The wireless communication device can determine a first estimate of a signal-to-noise ratio based on first estimates of a signal power and a noise power associated with the plurality of received data symbols. When the first estimate of the signal-to-noise ratio is below a predetermined threshold, a second estimate of the signal-to-noise ratio can be determined based on second estimates of the signal power and the noise power for the received data symbols. Other aspects, embodiments, and features are also included.