Search

In this paper, we study the performance of packet scheduling schemes for Ultra-Reliable Low-Latency Communications (URLLC) services. In order to ensure a low queuing time, we exploit the redundant coverage in many 5G Radio Access Networks (RAN) scenarios, where two frequency layers or Radio Access Technologies (RAT) are integrated. We consider three packet scheduling and redundancy schemes, namely Jointhe- Shortest-Queue (JSQ), systematic Redundancy (RED), and redundancy with Cancellation upon completion (CAN). On the basis of queuing theory results, we develop expressions for the reliability, defined as the probability that the packet is transmitted before some given target delay. We show that RED has a good performance at low load, while JSQ is better when the load increases; CAN outperforms all other schemes. We then show how the obtained results can be used for the dimensioning of needed 5G radio resources and discuss the trade-off between performance and implementation complexity.

We evaluate the throughput performance of a mobile network cell where device to device (D2D) communication, using part of the resource blocks of the considered cell, is used to offload the base station (BS) of part of its content delivery traffic. We suppose download requests occur according to a Poisson process from uniformly distributed user locations and are preferentially satisfied by one or more helpers whose number and positions are described by a Poisson process in the plane. We characterize optimal content placement for both regular caching, where sets of entire objects are cached by the helper devices, and coded caching, where each helper caches random coded chunks of certain objects such that a download may successively require several helpers and the BS. A multi-class processor sharing model is developed to determine the optimal resource partition between D2D and BS subsystems and evaluate the resulting throughput performance. Numerical results demonstrate significant capacity gains, notably for coded caching, that may well justify the added complexity of D2D communication.

We address the performance of a system where D2D communications add up to standard cellular traffic in future 5G networks. D2D resources are taken from the Uplink spectrum and, in this framework, two scheduling schemes are envisaged: the first one consists in two independent schedulers working on separate subsets of the Uplink channel, respectively dedicated to Uplink cellular communications and to D2D communications; the second one is a joint scheduler making use of the whole Uplink channel. In both schemes, all communications are scheduled, which in particular avoids the intra-cell interference issue. We propose multi-class Processor Sharing queueing models which account for realistic cellular radio conditions and provide traffic performance in terms of the average throughput for the different classes of flows. From the considered numerical scenarios, we conclude that the joint Uplink scheduling scheme provides better performance and allows D2D users to make an efficient use of their higher potential capacity, due to the device proximity. The corresponding throughput is also shown to be significantly higher than that perceived without any dedicated D2D link.

In this work, we develop tractable flow level performance models for data traffic in cellular networks when users are moving inside the cell and among cells. Due to mobility radio conditions may change during transfer and classical flow level models can no more be used. We first consider an exact Markovian model that models explicitly the mobility between zones of different radio conditions during the data transfer and derive performance metrics such as sojourn and downloading times. However, as this Markovian model does not scale with the number of radio conditions and the number of admissible users, we propose a closed-form approximation model, based on a multi-class Processor Sharing. Numerical results show that the proposed model provides a very tight approximation. We then use this model in order to study the impact of mobility on different performance metrics.

This paper investigates the network offloading capability of Device to Device (D2D) communication when combined with content caching. We consider a mobile network where a proportion of users are equipped with caches from which other users can retrieve contents using direct D2D communications. In this case, the offloading capacity depends both on the cache performance and the quality of the D2D links. As of the cache performance, we develop an analytical model for the cache hit rate for different content prefetching strategies. We then inject this hit rate in a queuing theory analysis of the network capacity where the macro base station and the D2D links are modeled as coupled Processor Sharing (PS) queues. We develop closed-form solutions for the stability region and the performance gains for both one-hop and two-hop D2D. Our simulation results illustrate the offloading capacity and present optimal cache and network parameters that maximize the benefit of D2D communications.

International audience; In this paper, we analyze the optimal blockwise subcarrier allocation scheme in coded Orthogonal Frequency Division Multiple Access (OFDMA) uplink systems without channel state information at the transmitter side. Due to the Discrete Fourier Transform, the subcarrier gains in OFDMA systems are correlated and this correlation plays a determinant role since it causes a degradation of the transmission performance. As a consequence, there exist some subcarrier allocation schemes which are preferable to achieve higher diversity gains. We propose the minimization of an inter-carrier sum-correlation function defined as the sum of correlations of each subcarrier with respect to the others in the same allocation scheme. We show the robustness of the proposed blockwise allocation policy to the effect of carrier frequency offsets (CFO). Moreover, we propose the block-size which provides the best trade-off between diversity and CFO for practical values of CFO. Finally, numerical simulations validating our results are presented.