Scheduling strategies for LTE uplink with flow behaviour analysis D. C. Dimitrova 1 , H. van den Berg, 1,2 , R. Litjens 2 , G. Heijenk 1 1 University of Twente, Postbus 217, 7500 AE Enschede, The Netherlands, {d.c.dimitrova,geert.heijenk}@ewi.utwente.nl 2 TNO ICT, The Netherlands, {j.l.vandenBerg,remco.litjens}@tno.nl Abstract. Long Term Evolution (LTE) is a cellular technology developed to sup- port diversity of data traffic at potentially high rates. It is foreseen to extend the capacity and improve the performance of current 3G cellular networks. A key mechanism in the LTE traffic handling is the packet scheduler, which is in charge of allocating resources to active flows in both the frequency and time dimension. In this paper we present a performance comparison of two distinct scheduling schemes for LTE uplink (fair fixed assignment and fair work-conserving) tak- ing into account both packet level characteristics and flow level dynamics due to the random user behaviour. For that purpose, we apply a combined analyti- cal/simulation approach which enables fast evaluation of performance measures such as mean flow transfer times manifesting the impact of resource allocation strategies. The results show that the resource allocation strategy has a crucial impact on performance and that some trends are observed only if flow level dy- namics are considered. 1 Introduction The 3rd Generation Partnership Project (3GPP) just recently finalized the standardiza- tion of the UTRA Long Term Evolution (LTE) with Orthogonal Frequency Division Multiple Access (OFDMA) as the core access technology. One of the key mechanisms for realizing the potential efficiency of this technology is the packet scheduler, which coordinates the access to the shared channel resources. In OFDMA-based LTE systems this coordination refers to both the time dimension (allocation of time frames) and the frequency dimension (allocation of subcarriers). These two grades of freedom, together with particular system constraints, make scheduling in LTE a challenging optimization problem, see [5]. Most research on LTE scheduling has been treating the downlink scenario, some examples being [8, 14]. Considerably less work has been dedicated to the uplink, where the transmit power constraint of the mobile equipment plays an important role. The LTE uplink scheduling problem can in general be formulated as a utility optimization problem, see e.g. [4, 7, 11]. The complexity of this optimization problem depends of course on the utility function that is considered (mostly aggregated throughput maxi- mization). Still other aspects, among which fairness requirements (e.g. short- or long- term throughput fairness) and specific system characteristics (e.g. regarding fast fading,