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In this paper, we focus on the scheduling problem in multi-channel wirelessnetworks, e.g., the downlink of a single cell in fourth generation (4G)OFDM-based cellular networks. Our goal is to design practical schedulingpolicies that can achieve provably good performance in terms of both throughputand delay, at a low complexity. While a class of $O(n^{2.5} \log n)$-complexityhybrid scheduling policies are recently developed to guarantee bothrate-function delay optimality (in the many-channel many-user asymptoticregime) and throughput optimality (in the general non-asymptotic setting),their practical complexity is typically high. To address this issue, we developa 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 achievesthroughput optimality, but also guarantees near-optimal asymptotic delayperformance. Specifically, we show that the rate-function attained by D-SSG forany delay-violation threshold $b$, is no smaller than the maximum achievablerate-function by any scheduling policy for threshold $b-1$. Thus, we are ableto achieve a reduction in complexity (from $O(n^{2.5} \log n)$ of the hybridpolicies to $2n^2 + 2n$) with a minimal drop in the delay performance. Moreimportantly, in practice, D-SSG generally has a substantially lower complexitythan the hybrid policies that typically have a large constant factor hidden inthe $O(\cdot)$ notation. Finally, we conduct numerical simulations to validateour theoretical results in various scenarios. The simulation results show thatD-SSG not only guarantees a near-optimal rate-function, but also empirically isvirtually indistinguishable from delay-optimal policies.

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