Semester

Spring

Date of Graduation

2017

Document Type

Problem/Project Report

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Lane Department of Computer Science and Electrical Engineering

Committee Chair

Matthew C. Valenti

Committee Co-Chair

Daryls S. Reynolds

Committee Member

Brian Woerner

Abstract

Effective transmission of data over a noisy wireless channel is a vital part of today's high speed technology driven society. In a wireless cell network, information is sent from mobile users to base stations. The information being transmitted is protected by error-control codes. In a conventional architecture the signal processing, including error-control decoding, is performed locally at each base station. Recently, a new architecture has emerged called Centralized Radio Access Network (C-RAN), which involves the centralized processing of the signals in a computing cloud. Using a computing cloud allows computational resources to be pooled, which improves utilization and efficiency. When the computational resources are finite and when the computational load varies over time, then there is a chance that the load exceeds the available resources. This situation creates a so-called computational outage, which has characteristics that are similar to outages caused by channel fading or interference. In this report, the computational complexity is quantified for a common class of error-correcting codes known as low-density parity check (LDPC) codes. To make the analysis tractable, a binary erasure channel is assumed. The concept of density evolution is used to obtain the complexity as a function of the code design parameters and the signal-to-interference-plus-noise ratio (SINR) of the channel. The analysis shows that there is a trade-off in that aggressively signaling at a high data rate causes high computational demands, while conservatively backing off on the rate can dramatically reduce the computational demand. Motivated by this trade-off, a scheduling algorithm is developed that balances the demands for high throughput and low computational outage rates.

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