ASSH: Designing Agile and Scalable Self-Healing Functionalities for Ultra Dense Future Cellular Networks

  • Cell densification is emerging as one of the key means to gain 1000x target capacity gain in the fifth generation (5G) cellular systems. This emerging reality poses a major challenge for the cellular industry: How to manage the susceptibility of an ultra-dense, extremely complex 5G network to a potentially high cell outage rate?
    Definition: A complete (or partial) cell outage is a scenario when either Base Station (BS) hardware and/or software malfunctions or when one or more cell parameters become misconfigured during network operations. Partial outage refers to scenarios when the cell continues to operate but its performance degrades below its typical level. In this proposal, the term cell outage refers to both partial and complete cell outages. The rate of outages is intrinsically proportional to cell density, and complexity of hardware and software that constitute the radio access network. Both of these factors have been consistently on rise from 1G to 4G, and trend is expected to continue for 5G. Currently,cellular carriers in the US alone currently spend over $15 billion annually to manage cell outages. In current cellular networks, drive tests or hardware fault alarms are employed for detecting cell outage; transitory cell outage compensation in the affected area is accomplished with makeshift cell-on-wheel. Such semi-manual approaches to cell outage management have proven inadequate and highly inefficient even for today’s operators, making them unfeasible for sustaining future cellular networks marked by ultra-dense cell deployment and mounting operational complexity. If no intervening measures are taken, cell outage management will be a primary challenge for future cellular networks, such as 5G.
    The ASSH project aims to address this challenge by developing an Advance Cell Outage Management (ACOM) framework for automating cell outage detection and compensation in future ultra-dense, heterogeneous cellular networks, thereby equipping them with fully self-healing functionality. ACOM integrates three novel schemes: 1) Autonomous highly agile, Macro Cell Outage Detection (MOD); 2) Autonomous Small Cell Outage Detection (SOD); and 3) Autonomous Heterogeneous Cell Outage Compensation (HOC). ACOM will provide solution for not only complete outages, which are easy to detect, but partial outages i.e. sleeping cells. Sleeping cells refer to scenarios where cells remain ON, but certain of its KPIs fall below the typical level.
    A large number of technical challenges are anticipated in development of ACOM. These challenges will be addressed by leveraging analytical tools from machine learning, big data analytics, optimization, chaos theory and game theory paradigms, by building on our past experience in this domain gained e.g. under QSON project.
    If this work sounds interesting, contact PI Ali Imran for collaboration opportunities.

    • Prof. Ali Imran (Principal Investigator- University of Oklahoma)
    • Hasan Farooq (PhD candidate - University of Oklahoma)
    • Ahmad Asghar (PhD candidate - University of Oklahoma)

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