Abstract:
A device receives, from a user device, a request to access a network, determines whether to accept or deny the request to access the network, and monitors traffic provided to or from the user device via the network. The device also determines a traffic pattern for the user device based on the traffic, classifies the traffic as one of high throughput traffic, low packet data size traffic, or high frequency packet interval traffic, and applies different network resource control mechanisms to different classifications of the traffic.
Abstract:
One or more devices determine uplink signal strength for a machine-to-machine (M2M) device using a wireless access network. The one or more devices identify a default uplink transmission mode that requires the M2M device to employ transmission time interval (TTI) bundling, when the uplink signal strength is below a particular threshold, and identify a default uplink transmission mode that requires the M2M device to not employ TTI bundling, when the uplink signal strength is not below the particular threshold. The one or more devices store, in a memory, the default transmission mode for the M2M device. The one or more devices retrieve, from the memory and during a wake-up time window associated with the M2M device, the default transmission mode for the M2M device and construct, for the M2M device, an uplink scheduling grant based on the stored default transmission mode.
Abstract:
A method may include obtaining traffic loading and resource utilization information associated with a network for the network time domain; obtaining machine-to-machine resource requirements for machine-to-machine tasks using the network; receiving a target resource utilization value indicative of a network resource limit for the network time domain; calculating a probability for assigning each machine-to-machine task to the network time domain, wherein the probability is based on a difference between the target resource utilization value and the traffic loading and resource utilization associated with the network; calculating a probability density function based on an independent and identically distributed random variable; generating a schedule of execution of the machine-to-machine tasks within the network time domain based on the probabilities associated with the machine-to-machine tasks and the probability density function; and providing the schedule of execution of the machine-to-machine tasks.
Abstract:
A device classifies access or control channel signals into a first class or a second class, initializes a dormancy timer associated with the device, and sets the dormancy timer to a default value. The device also sets a signal target utilization threshold, receives actual signals via the access or control channel, and identifies, when a number of the actual signals exceeds the signal target utilization threshold, a particular signal, from the actual signals, as belonging to the first class or the second class. The device further increases the default value of the dormancy timer when the particular signal belongs to the first class, and decreases the default value of the dormancy timer when the particular signal belongs to the second class.
Abstract:
A system may include a plurality of wireless devices, each wireless device including a time source and configured to selectively communicate with at least one other of the plurality of wireless devices by way of a packet-based time precision protocol. The plurality of wireless devices may include a first wireless device and a second wireless device, the first wireless device being configured to determine whether the first wireless device and the second wireless device are in selective communication over a single-hop wireless link; determine a one-way delay over the single-hop wireless link by way of at least one packed-based time precision protocol message; and calculate a distance measurement between the first wireless device and the second wireless device based at least in part on the one-way delay.
Abstract:
An approach is provided for interworking between radio access networks that utilize different radio access technologies. Loading information of a plurality of radio access networks that are accessible by a terminal is determined. A list of candidates from the radio access networks are output based on the loading information for use by the terminal.
Abstract:
A system may include a plurality of wireless devices, each wireless device including a time source and configured to selectively communicate with at least one other of the plurality of wireless devices by way of a packet-based time precision protocol. The plurality of wireless devices may include a first wireless device and a second wireless device, the first wireless device being configured to determine whether the first wireless device and the second wireless device are in selective communication over a single-hop wireless link; determine a one-way delay over the single-hop wireless link by way of at least one packed-based time precision protocol message; and calculate a distance measurement between the first wireless device and the second wireless device based at least in part on the one-way delay.
Abstract:
A device identifies mobile devices within a geographical area associated with a carrier network. The device further divides the geographical area into cells. The device also collects network statistics associated with the mobile devices. The device assigns values to the cells based on the network statistics, and identifies locations in which to place the small cells within the geographical area based on the values.
Abstract:
A method for measuring a call capacity of a cellular network which includes a plurality of sectors including a test sector and neighboring sectors defined by a number of base stations. A plurality of voice communication generators and a plurality of best effort generators are located both in the test sector and the neighboring sectors. Interference level from activated test units located within the neighboring sectors and the test sector represents total radio resources of the test sector. Throughput of best effort generators is measured while activating a predetermined number of voice communication generators within the test sector. An approximate relationship between the throughput of best effort generators and the number of activated voice communication generators is obtained. The call capacity within the test sector is determined from the approximate relationship between the throughput of best effort generators and the number of the activated voice communication generators. The call capacity within the test sector is adjusted to a real commercial communication environment based on real interference levels from the neighboring sectors.
Abstract:
A method may include obtaining traffic loading and resource utilization information associated with a network for the network time domain; obtaining machine-to-machine resource requirements for machine-to-machine tasks using the network; receiving a target resource utilization value indicative of a network resource limit for the network time domain; calculating a probability for assigning each machine-to-machine task to the network time domain, wherein the probability is based on a difference between the target resource utilization value and the traffic loading and resource utilization associated with the network; calculating a probability density function based on an independent and identically distributed random variable; generating a schedule of execution of the machine-to-machine tasks within the network time domain based on the probabilities associated with the machine-to-machine tasks and the probability density function; and providing the schedule of execution of the machine-to-machine tasks.