Optimal Pricing in a Rented 5G Infrastructure Scenario with Sticky Customers

Abstract

The ongoing deployment of 5G is accompanied by architecture and pricing decisions. Network sharing is a critical feature, allowing operators to reduce their costs, but introducing a mixed partnering/competition situation, where the infrastructure owner, renting out their infrastructure to virtual operators (who act as customers), also provides services to end customers, competing with virtual operators. Pricing is the leverage through which an optimal balance between the two roles is accomplished. However, pricing may not be the only variable affecting customers’ choice, which may prefer (stick to) one operator for several reasons. In this paper, we formulate a game model to analyse the optimal pricing decisions for operators in the presence of such sticky behaviour of customers. After concluding that the game does not allow for a Nash equilibrium, we consider a case when one of the parties (the infrastructure owner, the virtual operators, or the regulator) is responsible for setting prices and analyse how operators’ profits are impacted when price-setting powers are shifted among the parties. The scenario where the regulator sets prices leads to the lowest profits for the operators, even lower than when competitors set prices.

A Reinforcement Learning-Based Reverse Auction Enforcing Smart Pricing Policies towards B5G Offloading Strategies

“…These factors can be competition between telecom providers, demand-supply evaluations, client preferences, etc. In [24], Flamini et al and,in [25], Kim et al employed pricing algorithms that rely on strategic leverage and competition dynamics among operators in the telecoms industry. Operators optimize their prices to maximize their profit, taking into account factors such as client preferences and competition.…”