۱- Introduction and motivation

۲- Related work

۳- Problem statement

۴- A new efficient optimization algorithm

۵- Numerical results

۶- Conclusion

References

Abstract

This paper proposes a Branch-and-Cut algorithm for network operators and providers to propose a full coverage hole in the context of Cloud Radio Access Networks (C-RAN). In this context, and to optimize the network coverage when reducing interferences, network operators need new algorithms that enable to consolidate and re-optimize the antennas radii. This paper provides an NP-Hardness complexity proof of the full coverage hole problem and proposes a deep Branch-and-Cut algorithm based on the description of new cutting planes to accelerate the convergence time even for large problem sizes. Simulation results and comparison to the state of the art highlight the efficiency and the usefulness of our approach.

Background and definitions

With the era of programmable networks, TSPs are motivated by deploying more antennas to provide new network services with enhanced network coverage and connectivity. Indeed, this is feasible when embracing Cloud Radio Access Networks (C-RAN) technology described in the sequel (see Fig. 1). In this context, C-RAN is seen as a key enabler for the next generation mobile networks to handle the diverse service requirements. The main functionality of C-RAN (depicted in Fig. 1) consists in decoupling the BaseBand processing Unit (BBU) from the Remote Radio Head (RRH) to increase network coverage and reduce both the network CAPEX (CAPital EXpenses) and OPEX (OPerating EXpenses). Moreover, in C-RAN, network operators or service providers will propose more services to end users and this requires guaranteeing the network connectivity leveraging new approaches to reduce network holes (see Fig. 2) and to fulfill endusers requirements jointly. Thus, network operators have to investigate new approaches to rapidly reach a good tradeoff between interference elimination/reduction and coverage hole detection when embracing C-RAN technology. This work focuses on optimizing the full network coverage in CRAN by reducing the number of coverage holes and minimizing the inter-cell interferences. Indeed, to cope with this problem, numerous schemes have been proposed in different networks (e.g. sensor networks, . . .) using different approaches. Traditionally, and to guarantee the global coverage of a network, geometrical methods can be used under some conditions and constraints (see [1,2] for instance). These methods are based on the generalization of graphs to more generic combinatorial objects known as simplicial complexes and are made up of vertices, edges, triangles, tetrahedra and their n−dimensional counterparts. We define by k−simplex an unordered subset of k + 1 vertices. Thus, a 2−simplex is a triangle. In addition, and for sake of clarity, we note the existence of two approaches noted by Cech ˘ complex and Rips complex which are based on the verification of intersection between cells, to detect holes and connectivity problems (the detailed description of these complexes is not in the scope of this work, but more information can be found in [3]).