Achieving Optimal Throughput and Near-Optimal Asymptotic Delay Performance in Multichannel Wireless Networks With Low Complexity: A Practical Greedy Scheduling Policy

In this paper, we focus on the scheduling problem in multichannel wireless networks, e.g., the downlink of a single cell in fourth-generation (4G) OFDM-based cellular networks. Our goal is to design practical scheduling policies that can achieve provably good performance in terms of both throughput and delay, at a low complexity. While a class of
$O(n^{2.5}\log n)$
-complexity hybrid scheduling policies is recently developed to guarantee both rate-function delay optimality (in the many-channel many-user asymptotic regime) and throughput optimality (in the general non-asymptotic setting), their practical complexity is typically high. To address this issue, we develop a simple greedy policy called Delay-based Server-Side-Greedy (D-SSG) with a lower complexity
$2n^{2}+2n$
, and rigorously prove that D-SSG not only achieves throughput optimality, but also guarantees near-optimal asymptotic delay performance. Specifically, the rate-function of the delay-violation probability attained by D-SSG for any fixed integer delay threshold
$b>0$
is no smaller than the maximum achievable rate-function by any scheduling policy for threshold
$b-1$
. Thus, we are able to achieve a reduction in complexity (from
$O(n^{2.5}\log n)$
of the hybrid policies to
$2n^{2}+2n$
) with a minimal drop in the delay performance. More importantly, in practice, D-SSG generally has a substantially lower complexity than the hybrid policies that typically have a large constant factor hidden in the
$O(\cdot)$
notation. Finally, we conduct simulations to validate our theoretical results in various scenarios. The simulation results show that in all scenarios we consider, D-SSG not only guarantees a near-optimal rate-function, but also empirically has a similar delay performance to the rate-function delay-optimal policies.