  Cellular communication networks are plagued with redundant capacity, which
results in low utilization and cost-effectiveness of network capital
investments. The redundant capacity can be exploited to deliver secondary
traffic that is ultra-elastic and delay-tolerant. In this paper, we propose an
analytical framework to study the capacity-delay tradeoff of elastic/secondary
traffic in large scale cellular networks with spectrum aggregation. Our
framework integrates stochastic geometry and queueing theory models and gives
analytical insights into the capacity-delay performance in the interference
limited regime. Closed-form results are obtained to characterize the mean delay
and delay distribution as functions of per user throughput capacity. The
impacts of spectrum aggregation, user and base station (BS) densities, traffic
session payload, and primary traffic dynamics on the capacity-delay tradeoff
relationship are investigated. The fundamental capacity limit is derived and
its scaling behavior is revealed. Our analysis shows the feasibility of
providing secondary communication services over cellular networks and
highlights some critical design issues.
