Abstract:
Accurate calculation of the probability of outage for a cell within a CDMA network is utilized to relate cell coverage to cell capacity. Based on a desired probability of outage, the coverage of the cell may be calculated for an average number of users within the cell. The calculation is independent of the admission policy employed to achieve the specified average number of users. The resulting closed form expression for the tradeoff between coverage and carried traffic allows an optimal design of a CDMA network.
Abstract:
Provided herein is a computer-implemented method for generating an optimized cellular-network cell-site plan for an area. A plurality of cellular-traffic demand nodes distributed across the area is provided. Each cellular-traffic demand node of the plurality of cellular-traffic demand nodes has an associated weighting characteristics set. The plurality of nodes are consolidated into a plurality of centroids. Each centroid represents a number of nodes that come within a traffic threshold. A potential cell site is positioned on each of the centroids. Each potential cell site has an associated base-transmitter-station parameter characteristics set. The demand node coverage of each potential cell site is determined with respect to a signal strength of the potential cell site. From the plurality of potential cell sites a minimized cell-site subset is selected while maintaining sufficient cellular service coverage of the plurality of demand nodes.
Abstract:
Devices, systems, and methods for gathering, calculating and sending positioning information at a user device to one or more networks may be disclosed. In a first implementation the user device transforms pseudorange information relating to terrestrial beacons into GNSS pseudorange information. In a second implementation, the user device sends position information using GNSS information elements. In a third implementation, the user device sends position information using non-GNSS information elements.
Abstract:
Methods and apparatus for receiving, processing, and decoding MIMO transmissions in communications systems are described. A non-Gaussian approximation method for simplifying processing complexity where summations are used is described. Use of a priori information to facilitate determination of log likelihood ratios (LLRs) in receivers using iterative decoders is further described. A Gaussian or non-Gaussian approximation method using a priori information may be used to determine a K-best list of values for summation to generate an LLR is also described.
Abstract:
A method and apparatus for using information about a mobile terminal's location relative to a base station can improve performance of a communication system. In addition, information about the mobile terminal's velocity relative to the base station may be used to improve performance of the communication system. The location information may be used to estimate a nominal PN offset, and a set of PN offset to use, for processing communication signals. The velocity information may be used to estimate a nominal frequency of the communication signals.
Abstract:
The reliability of transmit power control (TPC) commands received from a transmitter is determined based on a TPC target value. The TPC target value is derived based on a TPC threshold and possibly a weight, depending on the receiver implementation. A received TPC command is considered reliable if its absolute value exceeds the TPC target value. Received TPC commands deemed as unreliable are discarded and not used for power control. Multiple TPC target values, used for detecting UP and DOWN commands, may be derived with multiple scaling factors. For a receiver in soft handover and receiving TPC commands from multiple transmitters, a different TPC target value may be derived for each transmitter. The received TPC commands for each transmitter are compared against that transmitter's TPC target value. Received TPC commands deemed as unreliable are discarded and not combined.
Abstract:
Systems and techniques are disclosed relating to wireless communications. These systems and techniques involve wireless communications wherein a device may be configured to recover an information signal from a carrier using a reference signal, detect a frequency error in the information signal; and periodically tune the reference signal to reduce the frequency error.
Abstract:
In one embodiment, the invention is directed toward frequency tracking techniques using control symbols that include both pilot and non-pilot symbols. For example, both the pilot and non-pilot symbols can be used in estimating frequency error of a received signal. The contribution of non-pilot symbols to the estimation can be weighted according to a confidence level associated with each non-pilot symbol. In some cases, soft decisions are generated for the non-pilot symbols and then used with the pilot symbols for frequency tracking. In this manner, the frequency tracking loop can be improved.
Abstract:
When all of the fingers of a wireless rake receiver are “out-of-lock,” the transmit power is initially maintained at a constant level. When the “out-of-lock” condition persists for an extended period of time, transmit power is increased in an effort to reacquire a lock with a subscriber unit or base station, as the case may be. An increase in transmit power may be effective in reacquiring lock when the cause of the out-of-lock condition is slow fading, rather than fast fading. Slow fading may be evidenced by persistence of the out-of-lock condition for an extended period of time. The length of the out-of-lock condition is used to selectively control transmit power and thereby promote quality of service. Transmit power is only increased when the fingers remain out-of-lock for an extended period of time, thereby avoiding undue increases in transmit power that could produce interference among different subscriber units.
Abstract:
The mobility of mobile subscribers within a wireless digital communications system is estimated based on highway maps and traffic data. Cells within the network are modelled as nodes connected by edges where neighboring cells are connected by roads. Each edge has two edge weight components representing traffic flow from one cell to the other and vice versa. The edge weight components are calculated from terrain factors based on the size or capacity of the roads connecting the two cells and the total traffic within the subject cell, which information may be obtained from commercial geographic databases and/or government agencies. The resulting edge weight represents an expected number of handoffs between the two cells. The problem of partitioning cells among available switches within the network is thus reduced to the purely mathematical problem of minimizing the total edge weights of edges intersected by the partition boundaries. Existing mathematical optimization techniques for optimizing node-edge systems may therefore be applied to reduce the total number of expected inter-switch handoffs as mobile subscribers pass from cell to cell within the network.