QoS-Aware Downlink Cooperation for Cell-Edge and Handoff Users

Abstract

In this paper, we present a quality-of-service (QoS)aware cooperative downlink scheduling approach for cell-edge and handoff users that offers more reliability and higher effective capacity. The cooperation (handoff) region is defined for active handoff users between two adjacent base stations (BSs) as a function of the user QoS requirements and network load. In addition, the proposed technique inherently acquires intercell interference (ICI) coordination by adjusting the position and size of the cooperation window suitably. Numerical results are presented showing reliability, user QoS and capacity gain performance, and the region for cooperative scheduling in a coded communication scenario. Our analysis indicates that cooperation provides relatively less gain in effective capacity, i.e., up to about 40% with respect to noncooperative handoff, when the QoS requirement is loose. On the other hand, when the QoS requirement is more stringent, the effective capacity gain can increase up to nearly 100%. Additionally, we show that, while for applications with a loose QoS requirement the cooperation window size is small, i.e., nearly 1% of the total area of the BSs participating in cooperation, it increases quite significantly, i.e., up to nearly 25%, for the applications with stringent QoS. Although the outage performance of the proposed approach is poorer than the joint transmission mode of a cooperative multipoint scheme in lightly loaded networks, its effective capacity is significantly higher under varying network traffic load and QoS constraints.Index Terms-Cooperative handoff, cooperation region-ofinterest, effective capacity, outage probability. 0018-9545

Vehicular Communications for 5G Cooperative Small-Cell Networks

“…x n , which is the sum of elements in the vector x kntnr−1 . In the end, the coverage probability of k cooperative small cell BSs can be expressed as an explicit form as (25).…”

“…To fully exploit benefits of heterogeneous networks, a radio resource allocation scheme was proposed for cooperative relays where the relay nodes with in-band backhaul act as micro BSs and are able to serve users either independently or cooperatively with macro cell BSs [24]. By defining the cooperation region as a function of the user quality of service (QoS) requirements and network load, a QoS aware cooperative downlink scheduling approach was proposed for cell-edge and handoff users that offers more reliability and higher effective capacity [25]. Using stochastic geometry-based heterogeneous cellular networks, the coverage probability, the average achievable rate and the energy efficient were derived for K-tier heterogeneous wireless networks with different cooperative sleep models for small cells [26].…”

On statistical power grid observability under communication constraints (invited paper)

“…To address these challenges, effective capacity (rate) theory is considered in this paper, which provides a cross‐layer model to estimate the statistical delay bound under channel fading scenarios. The effective capacity theory is a powerful analytical tool and can be applied as a quality of service provisioning metric in various communication systems, such as cellular networks [22], multi‐hop wireless networks [23] and cognitive radio networks [24]. Besides, in [25–27], the effective rates under various fading scenarios have been extensively studied, which makes the analysis based on effective rate readily applicable to the practical situations.…”

Unified Framework for the Effective Rate Analysis of Wireless Communication Systems Over MISO Fading Channels

“…In [2], the resource allocation and flow selection algorithms for video distribution over wireless networks have been studied based on the effective rate theory, where energy efficiency and statistical delay bound have been considered. In [3] and [4], scheduling algorithms have been studied for the multi-user time division downlink systems, exploiting the effective rate as the key to characterizing QoS constraints. In [5], the effective rate of two-hop wireless communication systems has been studied, where the impact of nodes' buffer constraints on the throughput has been considered.…”