Cloud Radio Access Networks (C-RANs) are an emerging technology that will lead to a leap forward in spectral and energy efficiency for next generation of 5G mobile networks. In traditional radio access networks, base stations are defined through a colocation of baseband units and radio heads, wherein the radio heads transmit and receive the radio signals, and the baseband units process the signals before transmission and after reception. C-RANs, on the other hand, consist of a large number of simple base stations that only have radio heads (RRUs), and aggregate the baseband units (BBUs) of multiple base stations together at central processing clouds that are connected to the radio-heads through optical fiber or microwave links.
Centralization of the BBUs allows for: (1) joint processing of signals that are collected by different RRUs, (2) utilization of multiple RRUs for transmission/reception to exploit diversity, (3) joint information processing, coding, and design of transmission strategies across multiple RRUs, and (4) information acquisition of channel conditions using a vast and dense collection of radio heads. This vision promises a significant step forward in spectral efficiency (e.g., through interference management or even interference utilization via sophisticated signal processing, optimal utilization of resources through joint coding) and energy efficiency (through reduction of energy consumption in processing and in communication) if challenges that threaten to thwart the large scale deployment of the technology can be surmounted.
The major goals of this project are: (1) To advance the theory and design of communication schemes for cloud radio access networks using cooperative strategies, (2) To make the proposed schemes scalable and robust by a merge of ideas from information theory and networking and by exploiting the structure of practical C-RANs in content requests and topology, and (3) Experimental validation using the ORBIT testbed for various explored C-RAN scenarios.
Results have been disseminated to information theory and networking communities. In particular, we have submitted one journal paper to Transactions on Information Theory (under review), and have published a paper in the journal of Transportation Research Part B: Methodological. Our work on V2V networks using the CRAN infrastructure was presented at Vehicular Technology Conference 2020.
The theoretical underpinnings of coordinated communications were also examined in the context of UAV missions between a group of UAVs and a ground control station (GCS), where the objective was to ensure the freshness of communication commands while facing potential communication interference. The problem was modeled as a game between the GCS and a group of UAVs, and a proportional fairness algorithm considering the aspects of maintaining a fair allocation of “freshness” amongst the UAVs was explored. A fixed-point algorithm that finds the equilibrium solution was derived, as were closed form solutions for a set of cases. Understanding how to maintain temporal freshness in cooperative communication scenarios is an important, emerging use case, particularly as the next generation of wireless applications will involve applications, like V2V, where tight control will be essential.