Low latency techniques for mobile backhaul over DOCSIS

Abstract

The mobile network operators (MNOs) are looking into economically viable backhaul solutions as alternatives to fiber, specifically the hybrid fiber coaxial networks (HFC). When the latencies from both the wireless and the HFC networks are added together, the result is a noticeable end-to-end system latency, particularly under network congestion. In order to decrease total system latency, we proposed a method to improve upstream userto-mobile core latency by coordinating the LTE and HFC scheduling in previous papers. In this paper, we implement and optimize the proposed method on a custom LTE and DOCSIS end-to-end system testbed. The testbed uses the OpenAirInterface (OAI) platform for the LTE network, along with Cisco's broadband router cBR-8 that is currently deployed in the HFC networks around the world. Our results show a backhaul latency improvement under all traffic load conditions.

STAR-RIS-Aided Mobile Edge Computing: Computation Rate Maximization With Binary Amplitude Coefficients

“…• Without-RIS: Without the deployment of an RIS, the equivalent channels in (2) and ( 7) contain only the direct link, i.e., h U r,k = h D r,k = 0, ∀k. We first study the relationship between the feasibility ratio [46] of the problem (13) and the target SINR γ D k with different benchmarks. The feasibility ratio of the problem ( 13) is defined as number of feasible simulations for (13) the total number of simulations .…”

“…To strike a good balance between communication power consumption, computation power consumption, and computation rate, we aim to maximize computation efficiency, defined as the ratio of total computation rate to total power consumption. This leads to the optimization problem being formulated as (13).…”

“…To enable cooperative transmission, the APs must either share the computation results of their respective users or each AP compute the results independently. Unfortunately, the computation results exchange between APs alone would cost 15 ms (for a lightly loaded network) to 50 ms (for a heavily loaded network) [13], [14], thus impractical for the latencycritical MEC applications such as mobile virtual reality and augmented reality, whose recommended total latency is around 20 ms [15]. Under the scenario that each cooperating AP independently computes the result for a serving user, more participating APs means more computation energy is spent in the hope of trading for less downlink transmission energy.…”

Security of 5G-Mobile Backhaul Networks: A Survey

“…Nowadays, the operators are focusing on the optimized use of a single network in multiple services as well as backhaul. The new mobile backhaul is moving from traditional technologies such as Time-Division Multiplexing (TDM), ATM, and Internet Protocol (IP)/Ethernet-based to technologies such as WiMAX-Long-Term Evolution (LTE), and 5G backhaul [14]. The mobile backhaul operators emphasized various key factors such as VPN-based services across the network, User traffic prediction, QoS, and high capacity with scalable and cost-effective setups to reduce the bottleneck problems.…”

Mobile-aware scheduling for low latency backhaul over DOCSIS

“…In previous papers [16] [17], we proposed a method to improve the upstream UE-to-mobile core latency by coordinating the LTE and DOCSIS scheduling operations. A 2-stage pipeline is formed with the LTE and DOCSIS schedulers.…”