Abstract: Methods and apparatus of monitoring cells in a wireless communication system may include determining existence of a condition for performing a cell search on a frequency. In addition, the methods and apparatus may include calculating an undetected energy-related value for a hypothetical undetected cell based on a measured energy-related value of each detected cell on the frequency in response to determining the condition for performing the cell search. The methods and apparatus may further include determining whether to perform the cell search based on the undetected energy-related value and a reselection criteria.

Abstract: A slot in a frame of n frames is received at user equipment (UE). Valid slots are detected based on a given validity criterion. The valid slots are classified as outage slots if an estimated signal quality does not exceed an outage signal quality. A total valid slot count and a total outage slot count are accumulated over an outer loop duration spanning a plurality of the slots. The total outage slot count is compared to a preset ratio of the total valid slot count. A target signal quality is updated based on the comparison.

Abstract: The described apparatus and methods may include a receiver configured to receive a signal, the signal being a combination of physical channel signals that each correspond to a different one of a plurality of physical channels, and a controller configured to capture signal energy from at least two of the physical channel signals, and detect a cell based on the captured signal energy.

Abstract: A method of data classification for use in a wireless communication system includes obtaining decoder metrics from a decoder. The decoder metrics correspond to data generated by the decoder. The decoder metrics include a first metric and a second metric. The method also includes classifying the data into a first category if the data fails an error detection check, into a second category if the data passes the error detection check and is determined to be unreliable, or into a third category if the data passes the error detection check and is determined to be reliable. A reliability of the data is determined based on at least one of the decoder metrics and a threshold.

Abstract: At least one feature pertains to a method of communication that comprises aligning a measurement task that utilizes a resource within a user equipment, such that at least a portion of the measurement task is performed during a time that the resource is enabled in the user equipment, and executing the measurement task during the time that the resource is enabled in the user equipment. In one example, the measurement task may be a searcher task, the resource may comprise receiver circuitry, and the time that the resource is enabled corresponds to a DRX monitoring interval of a downlink channel, such as a high speed shared control channel. By aligning and executing the searcher task during the time that the resource is enabled in the user equipment, searcher overhead may be reduced. Reducing searcher overhead allows the user equipment to save power by disabling the receiver circuitry.

Abstract: A method of data classification for use in a wireless communication system includes obtaining decoder metrics from a decoder. The decoder metrics correspond to data generated by the decoder. The decoder metrics include a symbol error rate (SER) and an energy metric (EM). The method also includes classifying the data into a first category if the data fails a cyclic redundancy check (CRC) check, into a second category if the data passes the CRC check and is determined to be unreliable, or into a third category if the data passes the CRC check and is determined to be reliable. A reliability of the data is determined based on the decoder metrics and an EM threshold.

Abstract: The described apparatus and methods may include a receiver configured to receive a signal, the signal being a combination of physical channel signals that each correspond to a different one of a plurality of physical channels, and a controller configured to capture signal energy from at least two of the physical channel signals, and detect a cell based on the captured signal energy.

Abstract: Techniques for performing searches by a user equipment (UE) equipped with multiple receive antennas are described. In an aspect, the UE may support multiple receive diversity (R×D) search modes. Each R×D search mode may be different from each remaining R×D search mode in how correlation is performed, how correlation results are combined, and/or how search results are reported for the multiple receive antennas. The UE may select an R×D search mode from among the multiple R×D search modes and may perform at least one step of a search in accordance with the selected R×D search mode. In another aspect, the UE may perform a search with interference cancellation to detect cell(s). The UE may determine multiple complex weights for multiple receive antennas such that signals from interfering cells can be attenuated. The UE may perform a search to detect cell(s) using the complex weights.

Abstract: A method and apparatus for improved initial cell acquisition with reduced frequency error impact. The method determines the slot timing of a transmission, identifies the primary scrambling code and frame timing using the common pilot channel, and provides a path profile using a pseudorandom noise (PN) search. An apparatus using a cell searcher that performs the method is also described.

Abstract: Techniques for predicting weights used for closed-loop transmit diversity. In a channel prediction scheme, channel gains for multiple transmit antennas are initially estimated (e.g., based on pilots received from these antennas) and used to derive predicted channel gains for a future time instant. The predicted channel gains are then used to derive predicted weights that are deemed to be “optimal” at the future time instant. Optimality may be determined based on one or more criteria, such as maximizing a received SNR for the received signals. In a weight prediction scheme, the channel gains for the multiple antennas are estimated and used to compute optimal weights for the current time instant. The current optimal weights are then used to predict the optimal weights at the future time instant. For both schemes, the prediction may be performed based on an adaptive filter (e.g., LMS or RLS filter) or a non-adaptive filter.

Abstract: A trellis decoder determines the most likely transmitted phase in response to previously requested phase adjustments and observed transmitted symbols. Maximum a posteriori (MAP) decoding also may be used. Alternatively, the identified likely transmitted phase is used for data demodulation. This and related features have the benefit of decreasing the effect of phase discrepancies introduced by erroneous reception of phase adjustment information, resulting in improved error rates, and a corresponding increase in system capacity, data throughput, or both.

Abstract: Techniques for predicting weights used for closed-loop transmit diversity. In a channel prediction scheme, channel gains for multiple transmit antennas are initially estimated (e.g., based on pilots received from these antennas) and used to derive predicted channel gains for a future time instant. The predicted channel gains are then used to derive predicted weights that are deemed to be “optimal” at the future time instant. Optimality may be determined based on one or more criteria, such as maximizing a received SNR for the received signals. In a weight prediction scheme, the channel gains for the multiple antennas are estimated and used to compute optimal weights for the current time instant. The current optimal weights are then used to predict the optimal weights at the future time instant. For both schemes, the prediction may be performed based on an adaptive filter (e.g., LMS or RLS filter) or a non-adaptive filter.

Abstract: A received symbol stream is oversampled and correlated with a known sync word to determine the correlation properties of the oversampled signal with a known sync word. A linear filter, such as a moving average window filter, is convolved with the correlation signal to generate a convolution signal. Once the convolution signal has reached a predetermined threshold, it is scanned over a predetermined window of oversamples. If the convolution signal exceeds the threshold for the window of oversamples, the sync word has been found and the symbol stream is down-sampled at intervals that depend on the data rate of the symbol stream. This down-sampling process may be done by picking the center oversample corresponding to each information symbol given the timing alignment, or by doing a majority vote over a multiple number of samples centered around the center oversample.

Abstract: Techniques for closed loop transmit diversity antenna verification are disclosed. In one aspect, a trellis decoder is used to determine the most likely transmitted phase in response to previously requested phase adjustments and observed transmitted symbols. In another aspect, maximum a posteriori (MAP) decoding is used. In yet another aspect, the identified likely transmitted phase is used for data demodulation. Various other aspects of the invention are also presented. These aspects have the benefit of decreasing the effect of phase discrepancies introduced by erroneous reception of phase adjustment information, resulting in improved error rates, and a corresponding increase in system capacity, data throughput, or both.

Abstract: A received symbol stream is oversampled and correlated with a known sync word to determine the correlation properties of the oversampled signal with a known sync word. A linear filter, such as a moving average window filter, is convolved with the correlation signal to generate a convolution signal. Once the convolution signal has reached a predetermined threshold, it is scanned over a predetermined window of oversamples. If the convolution signal exceeds the threshold for the window of oversamples, the sync word has been found and the symbol stream is down-sampled at intervals that depend on the data rate of the symbol stream. This down-sampling process may be done by picking the center oversample corresponding to each information symbol given the timing alignment, or by doing a majority vote over a multiple number of samples centered around the center oversample.