Communications, transmission of information, and Networks

Research in LIDS in the areas of communications, information transmission, and networks is centered on issues of performance (e.g., discovering fundamental limitations, and methods that come close to optimality), and scalability (e.g., informational and algorithmic efficiency as network size increases). It spans a broad range that includes:

  • Physical layer issues, e.g., wireless transmission technologies, resource allocation in wireless networks, wireline switching and scheduling, in conjunction with information theory, coding theory, and decoding methods. 
  • Information transport issues, e.g., routing, congestion control, and network management, building on stochastic network theory and optimization theory. 
  • Applications and services issues, e.g., network economics (based primarily on game theory), organization of ad hoc networks, sensor networks, peer-to-peer networks, and feedback control over networks. 

Some of the most exciting research in communications and systems and networks cuts across traditional disciplinary boundaries. Examples include:

  • Economic theory (especially game theory and mechanism design) to (i) study incentive systems that can induce socially desirable behavior on the part of the users, (ii) the effects of different pricing mechanisms, and (iii) the effects of different market structures. 
  • The interplay with systems and control theory. On the one hand, control theory provides insights and tools for the control of networks; on the other, there are several challenges in the field of control over networks, whereby feedback controllers operate in the presence of distributed and possibly delayed information that is delivered over a network infrastructure. Historically, LIDS has been instrumental in forming the modern (and now firmly established) view of communication networks, in terms of stochastic models and optimization-based approaches to resource allocation. 
  • Network science, an emerging discipline studying the structure and function of natural or engineered networks, by combining tools from graph theory, applied probability, statistical physics, economics, and game theory. 

Much of our research in this area is methodological, but also includes significant applied components.