Abstract: A communication system includes: a message communication module configured to communicate a preceding data before a repeat request; a metric module, coupled to the message communication module, configured to determine a repeat metric associated with the repeat request for re-communicating the preceding data or a portion therein; and wherein the message communication module is further configured to communicate a repeat data including a repeat portion based on the repeat metric for re-communicating the preceding data or a portion therein for communicating with a device.

Abstract: A wireless communication system includes: a control module configured to calculate a maximum throughput to represent a spectral efficiency; a storage module, coupled to the control module, configured to store the maximum throughput in a throughput table; and a communication module, coupled to the control module, configured to transmit a channel quality indicator as a feedback, selected from the throughput table, based on a largest value of the maximum throughput.

Abstract: One feature includes a method for implementing a fixed point recursive filter that reduces or eliminates steady state error. The method comprises obtaining a first filter state value, processing the first filter state value to remove a scaling factor to obtain a second filter state value, ascertaining that the recursive filter has reached a steady state, determining a nonlinear drift parameter based on a difference between the first filter state value and the second filter state value multiplied by the scaling factor, and adjusting the second filter state value with the nonlinear drift parameter to reduce steady state error of the recursive filter. Ascertaining that the recursive filter has reached the steady state may include determining that a filter output value at time n is equal to a filter output value at time n?1.

Abstract: A method, apparatus, computer program product, and processing system for generating a channel quality indicator (CQI) adapted according to the speed of a moving user equipment (UE). A CQI can be generated by mapping a calculated signal-to-noise ratio (SNR) to a CQI value. The SNR corresponds to a signal power and a noise power of a received pilot signal. The signal power and the noise power may be generated utilizing respective infinite impulse response (IIR) filters having filter coefficients chosen in accordance with the speed at which the UE moves. Selection of the filter coefficients can be made in accordance with a continuous function or a discontinuous function utilizing a threshold, and may utilize hysteresis.

Abstract: Various embodiments are disclosed which predict the channel quality indicator (CQI) in High Speed Downlink Packet Access (HSDPA). The accuracy of CQI is crucial for HSDPA performance. In some HSDPA systems the CQI may be as much as three (3) subframes stale. Accordingly, the prediction of CQI values is required in order to efficiently schedule data for transmission over the communication channel. Various embodiments disclose first order adaptive IIR filters which are significantly less complex than the finite impulse response (FIR) counterparts and achieve similar accuracy. By minimizing the mean squared error (MSE), an exact gradient descent algorithm may be used as well as two embodiment pseudolinear regression algorithms.

Abstract: A method for optimizing throughput in a wireless communication system is disclosed. A target metric is estimated based on previous acknowledgment data. A channel quality indicator offset is determined based on the target metric. A channel quality indicator is adjusted based on the channel quality indicator offset. The channel quality indicator indicates the quality of a wireless transmission channel.

Abstract: Techniques for deriving a channel impulse response estimate (CIRE) having improved quality are described. A first CIRE with multiple channel taps is obtained based on (1) an initial CIRE derived from a received pilot or (2) a filtered CIRE derived from the initial CIRE. In one aspect, the channel taps in the first CIRE are scaled with multiple scaling factors to obtain a second CIRE. For point-wise LMMSE scaling, the energy of each channel tap is estimated. The noise energy for the channel taps is also estimated, e.g., based on energies of channel taps on one or both edges of the first CIRE. Each channel tap is scaled based on a scaling factor determined by the energy of that channel tap and the noise energy. Each channel tap with energy below a threshold may be set to zero. In another aspect, the second CIRE is obtained by zeroing out selected ones of the channel taps in the first CIRE.