Abstract: The present disclosure generally discloses an autonomous localization capability configured to determine the localization of a mobile device of a wireless communication network based on a sequence of observations reported by the mobile device and a model that represents the motion and observations of mobile devices of the wireless communication network. The model that represents the motion and observations of the mobile devices may be a Hidden Markov Model (HMM) constructed based on use of localization information to define the hidden states of the and use of signal strength measurement reporting information to define possible observations. The localization problem for determining a localization of a given mobile device then becomes a maximum a posterior problem represented by the HMM, which may be solved using a particle filter based localization algorithm using localization probability distribution information which may be determined based on signal strength measurement reporting information.

Abstract: The present disclosure generally discloses an autonomous localization capability configured to determine the localization of a mobile device of a wireless communication network based on a sequence of observations reported by the mobile device and a model that represents the motion and observations of mobile devices of the wireless communication network. The model that represents the motion and observations of the mobile devices may be a Hidden Markov Model (HMM) constructed based on use of localization information to define the hidden states of the and use of signal strength measurement reporting information to define possible observations. The localization problem for determining a localization of a given mobile device then becomes a maximum a posterior problem represented by the HMM, which may be solved using a particle filter based localization algorithm using localization probability distribution information which may be determined based on signal strength measurement reporting information.

Abstract: At least one example embodiment discloses a method of controlling interference between a plurality of user equipments (UEs) in a network including a plurality of cells, each of the cells being at least one of a serving cell and neighboring cell. The method includes obtaining first path loss data of communications between the UEs and serving cells and second path loss data of communications between the UEs and neighboring cells, determining first parameters and nominal power parameters for the plurality of cells, respectively, based on the first path loss data and the second path loss data and determining nominal interferences for the plurality of cells, respectively, based on the respective first parameter and nominal power parameter.

Abstract: At least one example embodiment discloses a method of controlling interference between a plurality of user equipments (UEs) in a network including a plurality of cells, each of the cells being at least one of a serving cell and neighboring cell. The method includes obtaining first path loss data of communications between the UEs and serving cells and second path loss data of communications between the UEs and neighboring cells, determining first parameters and nominal power parameters for the plurality of cells, respectively, based on the first path loss data and the second path loss data and determining nominal interferences for the plurality of cells, respectively, based on the respective first parameter and nominal power parameter.

Abstract: The method includes assigning a priority to a mobile unit based on a Quality of Service (QoS) class associated with the mobile unit and a score associated with a user of the mobile unit.

Abstract: In one embodiment, the method includes receiving, at the communication node, resource usage price information. The resource usage price information characterizes a cost associated with the communication node using a resource. The communication node determines an amount of the resource to use based on the received resource usage price information.

Abstract: In one embodiment, mobile device traffic information and signal strength information associated with a geographical region are obtained. A plurality of candidate locations are determined based on the traffic information and the signal strength information, capacity values for each of the candidate locations are determined, and a candidate location is selected, from among the plurality of candidate locations, as a placement locations based on the capacity values.

Abstract: Embodiments of the claimed subject matter provide a method and apparatus for transforming signals for wireless communication. One embodiment of the apparatus includes a transformer comprising a plurality of first ports and second ports. Each first port is associated with a mode of a first antenna array configuration and each second port is configurable to be communicatively coupled to one of the antennas deployed in the first antenna array configuration. This embodiment also includes a selector configurable to select a subset of the modes of the first antenna array configuration based on a degree of variation with azimuth. This embodiment further includes a mapper configured to map each of a plurality of third ports to one of the first ports associated with one of the subset of modes. Each of the third ports is associated with a mode of a second antenna array configuration.

Abstract: The method includes determining one or more almost blank subframes (ABS) associated with a macro cell and associating a user equipment with one of the macro cell and a small cell using at least one of the one or more ABS based on one or more market prices associated with the small cell and the macro cell such that the determining and associating occurs jointly.

Abstract: The method includes determining one or more almost blank subframes (ABS) associated with a macro cell and associating a user equipment with one of the macro cell and a small cell using at least one of the one or more ABS based on one or more market prices associated with the small cell and the macro cell such that the determining and associating occurs jointly.

Abstract: Example methods use secondary scrambling codes in telecommunications networks. The secondary scrambling codes are assigned to mobile stations and channels used by mobile stations that are not adversely affected by the use of secondary scrambling codes. By assigning secondary scrambling codes additional users can utilize telecommunications networks with unique scrambling codes without reducing quality of service or increasing resource consumption. Example methods also reduce interference between mobile stations in the telecommunications networks.

Abstract: The method includes assigning a priority to a mobile unit based on a Quality of Service (QoS) class associated with the mobile unit and a score associated with a user of the mobile unit.

Abstract: A wireless communication system and joint beamforming method across multiple base stations for communicating with mobile stations. The wireless communication system communication system includes base stations and mobile stations. At least one of the base stations includes a joint beamformer controlling beamforming for the base stations. Each of the mobile stations receive information from the base stations, maintain a multiple-input and multiple-output active set (MAS) of base stations, and provide precoder weights to each of the base stations included in the MAS. The joint beamformer calculates joint beamforming weights for controlling communications between the base stations and mobile stations.

Abstract: Improvements are provided in an OFDM network that uses superposition coding. A broadcast signal and e.g. a unicast signal are each subjected to OFDM modulation including processing by an IDFT, combined, and transmitted using non-orthogonal transmission resources. In one approach, the respective signals are combined after instead of before the IDFT processing. In specific examples, a respective cyclic prefix is appended to each signal after the IDFT processing but before the respective signals are combined. In another approach, a broadcast pilot signal and e.g. a unicast pilot signal are transmitted concurrently with the broadcast and unicast information signals. The pilot signals are transmitted using the same time and subcarrier resources, but are made more distinguishable by combining each with a respective scrambling or spreading code. In specific examples, embodiments, the unicast pilot signal is used for estimating the data rate for transmission of further unicast information signals.

Abstract: In one embodiment, mobile device traffic information and signal strength information associated with a geographical region are obtained. A plurality of candidate locations are determined based on the traffic information and the signal strength information, capacity values for each of the candidate locations are determined, and a candidate location is selected, from among the plurality of candidate locations, as a placement locations based on the capacity values.

Abstract: One embodiment includes monitoring, for each communication node, at least one factor of interest and a plurality of potential influencing factors associated with the factor of interest. The factor of interest characterizes an operating condition of the communication node, and the plurality of potential influencing factors each have a potential influence on the operating condition. For each factor of interest for each communication node, a predictor coefficient for one or more of the potential influencing factors associated with the factor of interest is determined. The predictor coefficient indicates a predicted level of influence the potential influencing factor has on the factor of interest. For each communication node, interfaces are configured between the communication node and other communication nodes based on the determined predictor coefficients.

Abstract: To address the need to fairly allocate resources to a number of competing and heterogeneous consumers, embodiments such as those depicted in diagram 100 may be employed. A dynamic resource access (DRA) manager receives (101) a bid for a wireless resource from each bidder of a group of bidders, each bid including a bid price. Each bidder in the group of bidders is ranked (102) based on bid price and a quality of service associated with that bidder. The wireless resource is then allocated (103) to the highest ranked bidder of the group of bidders at the bid price of the second highest ranked bidder of the group of bidders.

Abstract: One embodiment includes monitoring, for each communication node, at least one factor of interest and a plurality of potential influencing factors associated with the factor of interest. The factor of interest characterizes an operating condition of the communication node, and the plurality of potential influencing factors each have a potential influence on the operating condition. For each factor of interest for each communication node, a predictor coefficient for one or more of the potential influencing factors associated with the factor of interest is determined. The predictor coefficient indicates a predicted level of influence the potential influencing factor has on the factor of interest. For each communication node, interfaces are configured between the communication node and other communication nodes based on the determined predictor coefficients.

Abstract: In one embodiment, the method includes receiving, at the communication node, resource usage price information. The resource usage price information characterizes a cost associated with the communication node using a resource. The communication node determines an amount of the resource to use based on the received resource usage price information.

Abstract: In one embodiment, a request is sent to a relay node (RN) requesting the RN to perform a signal measurement operation. The request includes an indication to measure a signal strength of a link between the RN and a user equipment (UE). A signal measurement value is received from relay node, a determination on whether to associate the UE with the RN is made based on the signal measurement value.