Research Interests

In general, I am working in the interface between telecommunications engineering and economics. Some indicative research areas include:

  • qualitative and quantitative techno-economic analysis of modern network architectures (cache-enabled networks, information-centric networks)
  • pricing and regulation in telecommunication markets
  • user-centric analysis of full-duplex communications
  • machine learning/big data analytics/network science
  • game-theoretic radio resource management (power control, channel access) in modern wireless networks (licensed spectrum sharing, device-to-device networks, small cell networks)

In the next paragraphs, I present a high-level description of some of the problems that I have studied along with the key contributions.

User-Centric Analysis of Full-Duplex Communications

  • The problem: We consider a full-duplex wireless network where each user can decide on his own whether he will use a full-duplex transmission (being able to transmit and receive at the same time using the same channel), half-duplex or wait. How often should each user choose each transmission mode and whether this set of choices will converge to a stable status?
  • Key contributions: We model the interactions of the users as a non-cooperative game where each user chooses a transmission mode with a certain probability. For a simple network, we show that there are infinitely many operating points where the set of probabilities of each user corresponds to a stable status (the so-called mixed Nash Equilibrium-MNE), characterise them analytically, and provide mechanism design hints on how to set the price of half-duplex and full-duplex transmissions to make them appealing from the single user’s perspective. Moreover, the optimality of MNE from a network-wide perspective is discussed, proving that the maximum aggregate throughput can indeed be reached at an equilibrium point. [Link to the paper.]

Pricing in Telecommunication Markets

  • The problem: We consider an oligopoly market where Mobile Service Providers (MSPs) aim to attract a pool of undecided users. How will the users choose a MSP and how the MSP's pricing policy influences his profit and his market share?
  • Key contributions: We introduce a metric for the user's decision by quantifying both the MSP price and the MSP reputation. For different classes of users, we provide conditions that capture their decision. Then, we derive the optimal MSP pricing policy that maximises either his market share or his revenue. For different scenarios of the knowledge of the market (users' preferences, pricing plans of the competition), we analyse the pricing strategy of a particular MSP in order to maximise his target. [Link to the paper.]
  • The problem: Consider two wireless cellular operators with a co-primary licensed spectrum access scheme, i.e., they jointly use a part (or the whole) of their licensed spectrum. Given that each operator charges his users with a usage-based pricing scheme, how can each operator increase his revenue?
  • Key contributions: We introduce a techno-economic approach, where the operators use bargaining and power control in order to control the interference of their users and, subsequently, increase their data consumption. We show that our approach leads to the socially optimal operating point, where the sum of the revenues of the operators is maximised, and we define bargaining strategies that guarantee that our scheme will lead to that point and also exhibit lower communication overhead and strictly larger revenue per operator than the state-of-the-art. [Link to the paper.]

Network Economics

  • The problem: We consider a scenario where an Internet Service Provider (ISP) serves users that choose digital content among M Content Providers (CP). Does the ISP have motivation to share the cost of deploying additional infrastructure with each CP? What happens when the CPs offer non-overlapping contents?
  • Key contributions: Regarding the first question, we derive conditions under which the ISP and the CP have motivation to form a coalition and share both the cost of deploying additional infrastructure (e.g., putting caches in the network) and the revenue that arises due to this infrastructure. We discuss how to share this profit in a fair and efficient way and show which is the investment policy that maximises the profit. Regarding the second question, we analyse how much each CP is willing to invest, capturing the negative externality of the competition to his expected profit. We show that the competition among the CPs will converge to a stable point with different level of investments per CP based on the Quality-of-Service that each one can offer and the users' market share. [Link to the paper.]
  • The problem: An operator is interested in adopting a future network architecture. Is it techno-economically better than the current Internet architecture?
  • Key contributions: We present the first network economic analysis of a particular information-centric networking architecture. We identify key technical factors that influence the operator's decision, we quantify the economical impact of each factor for both the current and the future network architecture and simulate the decision of the operator for a broad set of scenarios. Our analysis reveals that the initial deployment cost of the new architecture and the number of users that will adopt it are the key factors that define the decision of the operator. [Link to the paper.]

Radio Resource Management in Wireless Networks

  • The problem: Consider a wireless network where autonomous nodes aim at achieving their Quality-of-Service (QoS) targets but some of them fail. How can we increase the number of nodes that achieve their QoS targets without using an external entity as a referee?
  • Key contributions: We introduce bargaining and combine it with power control as a way to provide incentives to the wireless nodes to find more efficient operating points. We show that our distributed scheme can indeed find such points, demanding minimal cooperation among the nodes. Moreover, we show through simulations that it outperforms well-adopted approaches in terms of finding fair and efficient operating points. [Link to the paper.]
  • The problem: Consider a heterogeneous wireless network (e.g., a two-tier femtocell network) where nodes have different objective functions. Will the nodes coexist harmonically?
  • Key contributions: We model this setting as a non-cooperative game with all nodes applying power control. We show the existence of a stable operating point (the so-called Nash Equilibrium-NE) and derive conditions that guarantee its uniqueness. We present a distributed scheme that converges fast at the NE and we evaluate its efficiency through simulations showing that the payoff that the nodes receive at that NE is satisfactory in most scenarios. [Link to the paper.]
  • The problem: Consider a wireless network where each node decides on its own when and whether it will transmit. Will the nodes converge to an efficient operating point?
  • Key contributions: For simple network topologies, we show that such an operating point always exists. Moreover, we are able to explicitly compute these operating points, propose algorithms that converge to them and measure their efficiency providing upper and lower bounds of the performance gaps with respect to the optimal (centralized) solution. [Link to the paper.]