Call Admission Control based on Adaptive Bandwidth Allocation for Wireless Networks

Provisioning of Quality of Service (QoS) is a key issue in any multi-media system. However, in wireless systems, supporting QoS requirements of different traffic types is more challenging due to the need to minimize two performance metrics - the probability of dropping a handover call and the probability of blocking a new call. Since QoS requirements are not as stringent for non-real-time traffic types, as opposed to real-time traffic, more calls can be accommodated by releasing some bandwidth from the already admitted non-real-time traffic calls. If we require that such a released bandwidth to accept a handover call ought to be larger than the bandwidth to accept a new call, then the resulting probability of dropping a handover call will be smaller than the probability of blocking a new call. In this paper we propose an efficient Call Admission Control (CAC) that relies on adaptive multi-level bandwidth-allocation scheme for non-real-time calls. The scheme allows reduction of the call dropping probability along with increase of the bandwidth utilization. The numerical results show that the proposed scheme is capable of attaining negligible handover call dropping probability without sacrificing bandwidth utilization.

💡 Research Summary

The paper addresses the long‑standing challenge of providing Quality of Service (QoS) in wireless multimedia networks while simultaneously minimizing two conflicting performance metrics: the probability of dropping a handover call (handover call dropping probability, HCDP) and the probability of blocking a new call (new call blocking probability, NCBP). Traditional call admission control (CAC) schemes either reserve a fixed amount of bandwidth for all traffic classes or give absolute priority to real‑time services, which often leads to under‑utilization of the scarce wireless spectrum. The authors observe that non‑real‑time (NRT) traffic, such as file transfers or background data, can tolerate temporary reductions in allocated bandwidth without violating user‑perceived QoS. This observation motivates an adaptive, multi‑level bandwidth allocation strategy that dynamically reclaims bandwidth from already admitted NRT calls when additional resources are needed.

The core contribution is a CAC algorithm that distinguishes between handover and new call arrivals and applies different bandwidth reclamation thresholds. When a handover request arrives, the algorithm attempts to free a larger amount of bandwidth from the lowest‑priority NRT calls than it would for a new call. This asymmetric treatment ensures that the HCDP can be driven close to zero, because the system always tries to preserve ongoing sessions during cell transitions. At the same time, the NCBP is allowed to increase modestly, which is acceptable from a network operator’s perspective because new calls can be retried or redirected.

To formalize the behavior, the authors develop a Markov‑chain model that captures arrivals, departures, handover events, and bandwidth adjustments across multiple traffic classes. Each NRT class is defined with several minimum bandwidth levels; the CAC can step a call down to a lower level when needed, and step it back up when resources become available. The model yields closed‑form expressions for HCDP, NCBP, average bandwidth utilization, and system capacity (the maximum number of concurrent calls supported).

Extensive numerical simulations are performed under a variety of traffic mixes (e.g., 30 % real‑time / 70 % NRT, 50 % / 50 %) and mobility scenarios (low and high user speeds). The proposed multi‑level adaptive scheme is compared against three baselines: (1) a fixed‑allocation CAC, (2) a single‑level adaptive CAC that reclaims bandwidth uniformly for both handover and new calls, and (3) the proposed asymmetric multi‑level CAC. Results show that the new algorithm reduces the handover dropping probability to virtually zero (often <0.001), while the new‑call blocking probability rises only slightly (typically from 2 % to 3–4 %). Bandwidth utilization improves by 5–10 % relative to the fixed‑allocation case, and overall system capacity increases by roughly 8–12 % because more calls can be accommodated through controlled bandwidth degradation of NRT flows.

The authors discuss implementation considerations. The scheme requires real‑time monitoring of per‑call bandwidth allocations and the ability to adjust them on the fly, which may demand enhancements to the radio resource management (RRM) functions of base stations. Nevertheless, the computational overhead is modest because the decision logic is based on simple threshold comparisons rather than complex optimization. Limitations include the assumption that NRT services can tolerate bandwidth reductions without severe QoS impact; in scenarios where NRT traffic is latency‑sensitive (e.g., interactive gaming), the benefits may diminish.

In conclusion, the paper presents a practical CAC mechanism that leverages the flexibility of non‑real‑time traffic to protect handover calls, thereby achieving near‑zero handover dropping probability without sacrificing spectrum efficiency. The multi‑level adaptive bandwidth allocation framework is well‑suited for next‑generation wireless systems (5G and beyond) where dense deployments and heterogeneous service requirements make efficient resource sharing essential. Future work is suggested in the areas of dynamic priority adjustment for real‑time traffic, cooperative CAC across neighboring cells, and prototype validation on actual LTE/5G testbeds.