Overload control in the network domain of LTE/LTE-A based machine type communications

Abstract

It is expected that the LTE network, which includes the Radio Access Network (RAN) and the Core Network (CN) in 3GPP LTE systems, will be overloaded due to the huge number of Machine-Type Communication (MTC) devices in the near future. Overload in the RAN and CN of the LTE may result in congestion occurrence, resource waste, Quality of Service (QoS) degradation and in the worst-case, it will cause service unavailability. In this paper, we have proposed an adaptive mechanism to manage a large number of MTC devices in both RAN and CN of the LTE network. We use Access Class Barring (ACB) scheme to regulate the MTC traffic according to the congestions level in the RAN and CN. We consider a scenario in which two-priority-based classes of MTC devices are contending for the RAN resources. At first, the overload problem in the RAN is formulated to find the number of allowable contending MTC devices of each class taking into account their required QoS. Then, an active load management policy based on additive increase multiplicative decrease rule is proposed to control the incoming load from multiple cells to the CN. To effectively limit the number of MTC devices in both RAN and CN, in the proposed approach, each Evolved Node B updates the ACB factor upon overload detection in the RAN or CN in an adaptive manner. Simulation results show that the proposed mechanism is able to manage overload in the CN and RAN simultaneously.

Multiobjective cooperative swarm intelligence algorithm for uplink resource allocation in LTE‐A networks

“…In RAN and CN of the LTE network, Alavikia and Ghasemi 22 have proposed a technique named as an adaptive mechanism to manage an expansive number of MTC devices. To regulate the MTC traffic, they have utilized access class barring (ACB) scheme, as indicated by the congestions level in the CN and RAN.…”

“…From these values, until reaching the threshold values, the schedules were adjusted to discard the packets. When allocating the application to all users, the schedules met the delay 20 40 60 80 100 Users MCSIA-RA ACO-RA [21] PSA [22] ALS [26] TGSA [35] RR [36] PF [37] ACO-RA [21] PSA [22] ALS [26] TGSA [35] RR [36] PF [37] FIGURE 7 Packet delay comparison. ALS, adaptive LTE-Advanced cross-layer packet scheduling; MCSIA-RA, multiobjective cooperative swarm intelligence algorithm for resource allocation; PF, proportional fair; PSA, packet scheduling algorithm; RR, round robin and this delay is noted by using this proposed method, which computes the PLR and is necessary to analyze the packet delay budget.…”

“…Time consumption is 15% less than the ACO-PA, 19% less than PSA, 23% less than ALS, 29.1% less than TGSA, 32.7% less than RR, and 46.5% less than PF. 20 40 60 80 100 Users MCSIA-RA ACO-RA [21] PSA [22] ALS [26] TGSA [35] RR [36] PF [37] FIGURE 11 Time consumption comparison. ALS, adaptive LTE-Advanced cross-layer packet scheduling; MCSIA-RA, multiobjective cooperative swarm intelligence algorithm for resource allocation; PF, proportional fair; PSA, packet scheduling algorithm; RR, round robin…”

A multiple power level random access method for M2M communications in LTE‐A network

“…In the imperfect detection scenario, we assume that the eNB cannot detect the transmitted preambles by the MTCDs with probability q e . Figure 14 shows that at the detection error of q e = 0.2, the achieved throughput of both single power level FIGURE 14 The RA throughput of the perfect capture model against different values of N T for 3 considered scenarios when W max = 0, R max = ∞, and L = 1,2. MTCD indicates Machine-type Communication Device; RA, random access and 2 power level schemes is almost %20 less than their corresponding ideal throughput.…”

“…In the study of Ksentini et al, a Proportional‐Integral‐Derivative controller is proposed to adjust the ACB factor in order to control the congestion level in the core network node. The authors of one study apply the dynamic ACB factor to control the overload of MTCDs in both the radio access network and the core network of the LTE/LTE‐A, simultaneously. 3GPP also specified the Extended Access Barring (EAB) for M2M communications, where individual applications can be controlled through broadcasting RA information called System Information Block .…”