Abstract:
With a nonparametric G-Rake receiver, combining weights may be determined using a nonparametric mechanism in multiple-input, multiple-output (MIMO) scenarios. In an example embodiment, a method for a receiving device having a nonparametric G-Rake receiver entails calculating an impairment covariance matrix and determining combining weights. More specifically, the impairment covariance matrix is calculated based on a pilot channel using a nonparametric mechanism in a MIMO scenario in which a code-reuse interference term exists. The combining weights are determined for the nonparametric G-Rake receiver responsive to the impairment covariance matrix and by accounting for the code-reuse interference term.
Abstract:
A mobile receiver having a multi-mode interference suppression function and a way to estimate its speed utilizes a parametric approach to interference suppression at high speeds, and a nonparametric approach at low speeds. In particular, if the mobile receiver is currently operating in a nonparametric mode and its speed exceeds a first predetermined threshold, the mobile receiver switches to a parametric mode. Conversely, if the mobile receiver is currently in parametric mode and its speed is less than a second predetermined threshold, the mobile receiver switches to nonparametric mode. In one embodiment, the speed may be estimated by a Doppler frequency in the received signal, and the thresholds are Doppler frequencies. In one embodiment, the first and second thresholds are different, creating a hysteresis in the mode switching.
Abstract:
A time slot boundary of an unknown cell in a telecommunications system is identified by correlating a received signal with a known code over a range of delay values for each of one or more time slots, wherein the known code is used by all cells in the telecommunications system. Only for each of the delay values that are not associated with a known cell, correlation values obtained at each of the one or more time slots are accumulated. The time slot boundary is identified by determining which of the delay values is associated with a highest accumulated correlation value. One or more stored monitored delay sets may be used to determine which delay values are not associated with a known cell. The one or more stored monitored delay sets may be filtered using delay information obtained over a period of time.
Abstract:
A receiver utilizes pilot channel propagation channel estimates and a signal-to-interference metric derived from the pilot channel to form combining weights for use in obtaining soft symbols from a desired channel for subsequent decoding. The soft symbols thus obtained are substantially independent of the pilot channel amplitude.
Abstract:
The teachings herein disclose methods and apparatus that simplify impairment correlation estimation for received signal processing, based on determining, for any given processing interval, which impairment contributors should be considered in the estimation of overall received signal impairment correlations. These simplifications reduce computational processing requirements, allowing reduced circuit complexity and/or reduced operating power, and improve receiver performance. A corresponding transmitter and transmission method include transmitting multiple information streams to targeted receivers according to ongoing scheduling, and controlling the ongoing scheduling to reduce the number of impairment contributors considered in impairment correlation estimation at the targeted receivers. In one embodiment, a receiver identifies which impairment contributors to consider based on receiving control information. In another embodiment, the receiver identifies the impairment contributors to consider based on background processing, e.g., background determination of parametric model fitting parameters for a plurality of impairment contributors, and observing those model fitting parameters over time.
Abstract:
A power control unit (500) for a power control system in a mobile communication system, the power control unit (500) comprising an inner power control loop element (503, 507), which generates a transmit power control command (504), and an outer power control loop element (516) connected to the inner power control loop element (503, 507), the outer power control loop element (516) being configured for providing a target value (506) to the inner power control loop element (503, 507). The outer power control loop element (516) comprises a soft information estimator (509) connected to at least one outer loop regulator (501, 502), wherein the soft information estimator (509) is configured to provide a soft information estimate (510) to the at least one outer loop regulator (503).
Abstract:
Log-likelihood ratios produced by a decoder are incorporated into a soft symbol to soft bit estimation process and are used to perform improved channel estimation and impairment covariance estimation. In an example method, a plurality of soft bits and corresponding probability metrics for a series of received unknown symbols are generated. Estimates of the received unknown information symbols are then regenerated, as a function of the soft bits and corresponding probability metrics. An estimate of the average amplitude of the received unknown information symbols, or an estimate of the propagation channel response experienced by the received unknown information symbols, or both, are calculated, as a function of the regenerated symbol estimates. The results are applied to produce demodulated symbols for a second decoding iteration for the series of received unknown symbols.
Abstract:
A set of channelization codes to be monitored is divided into two groups. The first group includes those codes for which an associated symbol modulation and transmit-diversity scheme is known. In the second group are those codes that are characterized by an unknown symbol modulation or unknown transmit-diversity scheme. The quality of the transmission of each code is then evaluated, using a metric. The metric in turn is used to determine whether the code should be used in estimating the covariance matrix by correlating the RAKE data corresponding to the code (i.e., by computing a correlation matrix for the code) or by first subtracting the channel estimates from the channel samples before correlation (i.e., by computing a covariance matrix for the code). An impairment covariance matrix is computed from the covariance matrices and correlation matrices so computed.
Abstract:
In one aspect, the present invention provides for blindly detecting the presence of one or more secondary pilot signals that are not being used to serve a communication apparatus, such as a User Equipment (UE). Among its several advantages, the approach to blind detection taught herein provides robust detection performance, yet it requires relatively few receiver resources. The contemplated apparatus, in at least one example embodiment, uses its blind detection of secondary pilot signal(s) to trigger suppression of secondary pilot interference, for improved reception performance. In a particular, non-limiting example, the apparatus operates in an HSDPA-MIMO network in a non-MIMO mode and blindly detects secondary pilot signal energy associated with the supporting network providing MIMO service to nearby equipment.
Abstract:
Log-likelihood ratios produced by a decoder are incorporated into a soft symbol to soft bit estimation process and are used to perform improved channel estimation and impairment covariance estimation. In an example method, a plurality of soft bits and corresponding probability metrics for a series of received unknown symbols are generated. Estimates of the received unknown information symbols are then regenerated, as a function of the soft bits and corresponding probability metrics. An estimate of the average amplitude of the received unknown information symbols, or an estimate of the propagation channel response experienced by the received unknown information symbols, or both, are calculated, as a function of the regenerated symbol estimates. The results are applied to produce demodulated symbols for a second decoding iteration for the series of received unknown symbols.