Attaining the New Frontier of Spectral Efficiency with Tradeoffs in Computation Through Cloud Radio Access Networks (NSF award #1850356 )
In the next generation of 5G mobile networks, cloud radio access networks (C-RANs) are among the most promising technologies to attain a leap forward in spectral efficiency. This architecture was first proposed by IBM [4] and China Mobile [5], and it combines advances in both wireless networks and cloud distributed processing. In traditional radio access networks, base stations are defined through a co-location of baseband units and radio heads, the radio heads transmit and receive the radio signals, and the baseband units process the signals before transmission and after reception. The baseband unit at a base station has access only to the signals that the radio head at the corresponding base station handles. In a fundamental paradigm shift, C-RANs employ a large number of simple base stations that consist only of radio heads (RRUs), and aggregate the baseband units (BBUs) of multiple base stations together at central processors, connected to the RRUs through optical fiber or microwave links. The centralization of the BBUs allows for utilization of multiple RRUs for transmission to and reception from users to exploit diversity, joint information processing, coding, and design of transmission strategies across multiple RRUs to share spectrum. The vision of centralized processing and high density transmission promises spectral efficiency if challenges that thwart the large scale deployment of CRANs can be surmounted. We will realize this vision through a cross-layer investigation of C-RAN technology.
Our Team
Shirin Saeedi Bidokhti (PI)
University of Pennsylvania
Saswati Sarkar (Co-PI)
University of Pennsylvania
Wade Trappe (Co-PI)
Rutgers University
Jungyeol Kim (PhD student))
University of Pennsylvania
Xiaoran Fan (PhD student)
Rutgers University
Xingran Chen (PhD student))
University of Pennsylvania
Research Activities
Thrust I: Theory and Code Design
Our goal is to advance the theory and code design for spectral efficiency
using C-RANs. We propose coding strategies that utilize the fronthaul network to
transmit users’ information and facilitate coordination among RRUs. Coordination is
essential in tackling multi-access interference over C-RANs. Moreover, it turns out that there are fundamental tradeoffs between coordination
and rate which we seek to mathematically characterize. For the proposed schemes to be practical, we aim to also address the issue of synchronization through new models and/or methods that ensure timely communication.
Some of our past and present research directions are:
- Coordinated communications for different demands (UPenn)
- Conferencing in CRANs (UPenn)
- Tradeoffs between rate and coordination (UPenn)
- Latency-distortion tradeoff of broadcast erasure networks (UPenn)
- Freshness of distributed and cooperative communications (UPenn, Rutgers)
Thrust II: Scalable and Robust Network Strategies
To move towards practical C-RANs, we need scalable and robust strategies.
Today’s networks are too large for fully coordinated coding, and thus we will exploit
the structure of practical C-RANs in content requests and topology, and propose suboptimal
schemes that use coordinated coding as a building block (designed for simpler
networks) and devise network layer scheduling strategies on them to obtain improved
performance. Using this approach, we will find tradeoffs between spectral efficiency
and computational complexity and devise practical schemes to attain them.
Some of our past and present research directions are:
- Applications in vehicular networks (UPenn)
- Scheduling for coordinated communication (UPenn)
Thrust III: Experiments
Our research is also focused on validating its assumptions and models. Experiments
will be conducted on Rutger's ORBIT testbed for various explored C-RAN scenarios.
Some of our past and present research directions are:
- Synchronization in coordinated communications (Rutgers)
- Collaborative Intelligent Radio Networks (CIRN) (Rutgers)
Publications