International Business Machines Corporation

Ittiam Systems (p) Ltd.

Parul Gupta

Ravindranath Kokku

Dinesh C Verma

Kang-Won Lee

Shivkumar Kalyanaraman

Ramya Raghavendra

Vinay Kumar Kolar

Malolan Chetlur

Umamaheswari C Devi

Bong Jun Ko

Ravi Kothari

Petros Zerfos

Mukundan Madhavan

Shobha Ramaswamy

Mohit Agarwal

A computer-implemented method includes: receiving, using a processor, multiple data session records (DSRs); storing the multiple DSRs in a memory communicatively coupled to the processor; analyzing, using the processor, the stored multiple DSRs for temporal and spatial data; and determining, using the processor, quality degradation by using the temporal and spatial data for the stored multiple DSRs.

Detecting and diagnosing call quality degradation issues using data session record data

Various embodiments provide adaptive monitoring of a wireless communication network. In one embodiment, a first set of network data generated for a wireless communication network is analyzed. The first set of network data is a set of historical network data for the wireless communication network. A baseline for at least one operating characteristic associated with the wireless communication network is determined based on the analyzing. A second set of network data generated for the wireless communication network is received. The second set of call detail records that has been received is utilized to determine if the at least one operating characteristic corresponds to the baseline. A set of monitoring operations performed by a network management system with respect to the wireless communication network is dynamically adjusted based on the at least one operating characteristic failing to correspond to the baseline.

Adaptive monitoring for cellular networks

Various embodiments monitor user mobility in a wireless communication network. In one embodiment, a set of temporally related call detail records associated with at least one user of a wireless communication network is analyzed. A set of base stations accessed during at least one call associated with the set of temporally related call detail records is identified based on the analysis of the records. At least one road segment of a road network within a threshold distance to each of the set of base stations is identified. A set of mobility information for the at least one user indicating that the at least one user traversed the at least one road segment is stored based on identifying the at least one road segment.

Correlating road network information and user mobility information for wireless communication network planning

Various embodiments manage service issues in a wireless communication network. In one embodiment, a plurality of call detail records associated with a wireless communication network is received. The plurality of call detail records is analyzed. At least one pattern from the plurality of call detail records is identified based on analyzing the plurality of call detail records. The at least one pattern indicates at least one service issue occurred during a set of calls associated with each of the plurality of call detail records. A location associated with the at least one service issue that has occurred is identified based on identifying the at least one pattern.

Detecting cellular connectivity issues in a wireless communication network

Methods and arrangements for characterizing software base-station workloads. Input system parameters are mapped to work-determining parameters which act to determine computational requirements of a dynamic workload. A synthetic experiment is undertaken to measure the computational requirements determined by the work-determining parameters.

Characterization of real-time software base-station workloads at fine-grained time-scales

Systems and associated methods for estimating wireless workloads are described herein. Systems and methods provide for generating an estimate of a wireless workload's processing requirements from the combined knowledge of system specific values, such as system parameters, platform details, and implementation details. Systems and methods for estimating wireless workloads may be utilized in various wireless protocols, including, 3G, WiMax, LTE, WiFi, femtocells, and point-to-point wireless links. The estimated workloads may be used for scheduling wireless workloads in a shared computing environment.

Estimating processing workloads

Systems and methods for estimating processing workloads

Systems and methods for effecting delayed delivery of data. There are received, at a scheduler, from a plurality of mobile computing devices, a plurality of requests for transmission of data objects. Responsive to the requests, communication is made to at least one of the devices at least one offer for a delayed transmission deadline of at least one data object. There is received, at the scheduler, at least one response to the at least one offer, and there is determined a scheduling priority of transmissions based on the at least one response.

Delayed data delivery options

A technique for improving the performance of OFDM (Orthogonal Frequency Division Multiplexing) systems addresses the Sampling Frequency Offset (SFO) estimation and correction problems of conventional techniques and provides improved performance in a wide range of operating conditions. The technique teaches a correction scheme that uses known pilots in each OFDM symbol to estimate slope of phase error and subsequently calculate the correction factor for each of the sub-carriers in the associated OFDM symbol. The present subject matter further teaches an averaging slope estimates over a window of predetermined number of OFDM symbols to average out noise and get a refined correction factor. In addition, the present technique teaches tracking rate of growth of slope across OFDM symbols to estimate SFO, which can be used for the timing error correction in the time domain.

Pilot based sampling frequency offset estimation and correction for an OFDM system

A method (and algorithm) for detection of 802.11a and 802.11b frames in an 802.11 transmission, calculates DCC (delayed copy correlation) and LCC (local copy correlation) magnitudes and compares their normalized values with threshold values. When a signal is detected, (i.e., AGC locks) the algorithm checks for a valid 802.11a frame, and it exploits the DCC properties of the received symbols. Because of the repetitions of short preambles in received symbols, the DCC is high when the short preamble symbols are present. Further, 802.11b detection may be based on Barker correlation properties simultaneously. A counter array is maintained for each position in a Barker window, and is incremented if the normalized LCC of the incoming sequence with the Barker code exceeds a threshold. An 802.11b packet is declared if the maximum value of the counter array exceeds a predetermined number in a specified number of Barker windows.

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Bengaluru, India

Parul Gupta