Ursula Challita

On LTE-WiFi coexistence and inter-operator spectrum sharing in unlicensed bands: altruism, cooperation and fairness

The coexistence of LTE-Unlicensed (LTE-U) and WiFi in unlicensed spectrum is studied in the context of airtime sharing. We consider core problem where a set of LTE-U cells from different operators share the same channel as a co-located WiFi access point (AP). We assume that LTE-U cells utilize Listen-Before-Talk (LBT) as the default channel access mechanism. Principally, we deal with the following question: how should an operators LTE-U cell adjust its contention window in order to provide a fair coexistence both with WiFi and co-located LTE-U cells of other operators? We consider that LTE-U cells behave altruistically both among themselves and to WiFi. Cooperation of LTE-U cells is studied using a coalition formation game framework which is based on the well-known Shapley value. We define a payoff configuration scheme in the coalition game which involves altruism. We prove that the coalitional game is always zero-monotonic, and Shapley value is also max-min fair. We compare airtime sharing performance of Shapley value with weighted proportional fairness via numerical results and show that Shapley value provides much better fairness than proportional fairness as determined by entropy and Jains index metrics while having roughly equal average airtime.

A chance constrained approach for LTE cellular network planning under uncertainty

With the evolution towards 4G cellular networks, there is a need to develop new approaches for radio network planning?(RNP) that can capture the technology enhancements to determine optimized locations and configurations of base station sites. Conventional RNP approaches are normally based on a deterministic link budget analysis that compensates for signal statistical variation via pre-determined power margins; this is normally followed by Monte-Carlo simulations to fine tune the planning outcome. In this work, we present a novel approach for cellular RNP that captures the uncertainty in signals and interference as part of the problem formulation leading directly to an optimized planning solution; the approach is generic and can capture signal uncertainty due to fading and dynamic resource allocation with possible extension to other adaptive system features. The approach is divided into two parts that are addressed separately using chance constrained optimization and then combined within a common framework. The first part, denoted as site selection problem, aims at selecting the minimum cardinality set of eNodeBs from a given large set, that satisfies target performance requirements. The second part, denoted as site placement problem, aims at refining the locations of the selected eNodeBs in order to further enhance the planning quality. Finally, both parts are combined within a common framework to determine the optimized number and locations of eNodeBs over a given geographical area based on a wide range of system and user parameters. A divide and conquer approach is also proposed to deal with the complexity of planning large network scenarios. Performance results are presented to highlight the effectiveness of the proposed framework with detailed analysis and verification via Monte-Carlo simulations.

Holistic Small Cell Traffic Balancing across Licensed and Unlicensed Bands

Due to the dramatic growth in mobile data traffic on one hand and the scarcity of the licensed spectrum on the other hand, mobile operators are considering the use of unlicensed bands (especially those in 5 GHz) as complementary spectrum for providing higher system capacity and better user experience. This approach is currently being standardized by 3GPP under the name of LTE Licensed-Assisted Access (LTE-LAA). In this paper, we take a holistic approach for LTE-LAA small cell traffic balancing by jointly optimizing the use of the licensed and unlicensed bands. We pose this traffic balancing as an optimization problem that seeks proportional fair coexistence of WiFi, small cell and macro cell users by adapting the transmission probability of the LTE-LAA small cell in the licensed and unlicensed bands. The motivation for this formulation is for the LTE-LAA small cell to switch between or aggregate licensed and unlicensed bands depending on the interference/traffic level and the number of active users in each band. We derive a closed form solution for this optimization problem and additionally propose a transmission mechanism for the operation of the LTE-LAA small cell on both bands. Through numerical and simulation results, we show that our proposed traffic balancing scheme, besides enabling better LTE-WiFi coexistence and efficient utilization of the radio resources relative to the existing traffic balancing scheme, also provides a better tradeoff between maximizing the total network throughput and achieving fairness among all network flows compared to alternative approaches.