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Long term evolution-wireless local area network (LTE-WLAN) aggregation (LWA) has recently emerged as a promising third generation partnership project (3GPP) Release 13 technology to efficiently aggregate LTE and WLAN at the packet data convergence protocol layer, allowing uplink traffic to be carried on LTE and downlink on both LTE and WLAN. This removes all the contention asymmetry problems of WLAN and allows an optimum usage of both licensed and unlicensed band for downlink. In this paper, we present a new feature of LWA, its flow control scheme, which controls how to aggregate downlink traffic in licensed and unlicensed bands. This aggregation technique exploits user equipment-based flow control feedback in the form of LWA status reports, and can be expanded to work with any number of frequency bands and radio technologies. The same concepts apply to 5G networks, although the performance evaluation provided here is in the context of LTE-Advanced Pro. Simulation results in a typical enterprise scenario show that LWA can enhance user performance up to 8 times over LTE-only, and 3.7 times over WLAN only networks, respectively. The impact of the file size and LWA status report frequency on network performance is also investigated. INDEX TERMSCellular networks, long term evolution (LTE), wireless local area network (WLAN), LTE WLAN aggregation (LWA), flow control, aggregation.

Spectrally-spatially flexible optical networks (SS-FONs) are proposed as a solution for future traffic requirements in optical backbone networks. As SS-FONs operate within flexgrid, the provisioning of lightpaths spanning multiple frequency slots results in spectrum fragmentation, especially in presence of dynamic traffic. Fragmentation, in turn, may lead to blocking of dynamic requests due to the lack of sufficiently-large free spectral windows. In this paper, to reach a better understanding of fragmentation in SS-FON, we extend several metrics used in (singlecore) elastic optical networks to measure the fragmentation in SS-FONs. Next, we apply these metrics to a dynamic-routing algorithm with the goal of minimizing bandwidth blocking. Finally, we analyze the impact of spatial continuity constraint (SCC) on the network fragmentation. Simulations run on two representative network topologies show that the root mean square factor metric yields the best performance in terms of blocking when compared to other analyzed metrics.