In this contribution, we jointly investigate the benefits of caching and interference alignment (IA) in multiple-input multiple-output (MIMO) interference channel under limited backhaul capacity. In particular, total average transmission rate is derived as a function of various system parameters such as backhaul link capacity, cache size, number of active transmitter-receiver pairs as well as the quantization bits for channel state information (CSI). Given the fact that base stations are equipped both with caching and IA capabilities and have knowledge of content popularity profile, we then characterize an operational regime where the caching is beneficial. Subsequently, we find the optimal number of transmitter-receiver pairs that maximizes the total average transmission rate. When the popularity profile of requested contents falls into the operational regime, it turns out that caching substantially improves the throughput as it mitigates the backhaul usage and allows IA methods to take benefit of such limited backhaul. Index Termsedge caching, interference alignment, limited backhaul, wireless networks, 5G cellular networks.

Low latency targets for Ultra-Reliable Low Latency Communications (URLLC) may be conflicting with their stringent reliability requirements due to the need for re-transmissions. We explore in this paper the different resource allocation schemes for transmissions and re-transmissions depending on the requirements of the underlying service and on the traffic characteristics, focusing on Industrial Internet of Things (IIoT). We namely consider schemes with individual reservation versus a pool of contention-based reserved resources. We provide novel resource allocation schemes for initial transmissions and re-transmissions and derive corresponding analytical models for loss rates. We then show how to set the system parameters that allow meeting the URLLC requirements with low resource consumption.

This work studies the problem of feedback allocation and scheduling for a multichannel downlink cellular network under limited and delayed feedback. We propose two efficient algorithms that select the link states that should be reported to the base-station (BS). A novelty here is that these feedback allocation algorithms are performed at the users' side to take advantage of their local CSI (channel state information) knowledge in order to achieve higher gains. The first algorithm is suitable for a continuous-time contention scheme and requires only one feedback per channel, whereas the second one is adapted for a discrete-time contention scheme and adopts a threshold-based concept. For this second algorithm, we study some implementation aspects related to the feedback period and investigate the trade-off between knowing at the BS a small number of accurate link states and a larger but outdated number of link states. We show that these algorithms, combined with the Max-Weight scheduling, achieve good stability performance compared with the ideal system. I. INTRODUCTION In this work, we address the problem of joint feedback reporting and scheduling for multiuser downlink wireless networks employing multiple parallel channels, i.e. multicarrier technique, to serve the users. Such a setting corresponds for example to a single cell orthogonal frequency-division multiplexing access (OFDMA) scheme, which is implemented in the long term evolution (LTE) standards [2] and was shown to deliver a substantial increase in the system's performance; OFDMA is also the multiple access technique adopted for 5G systems. To exploit multiuser diversity in multichannel downlink networks, the base station (BS) needs to acquire channel state information (CSI) from users. These CSIs are usually unknown at the BS, especially in frequency-division duplex (FDD) systems which lack of channel reciprocity. A common method to acquire the downlink CSI is to allocate a M. Deghel and M. Assaad are with the TCL Chair on 5G, Laboratoire de Signaux et Systèmes (L2S, UMR8506), CentraleSupélec,

This work proposes a new joint link adaptation and HARQ (Hybrid Automatic Repeat Request) scheme for URLLC (Ultra-Reliable Low-Latency Communication) services. We consider the case where the transmitter knows only the average SNR (Signal-to-Noise Ratio) and not the instantaneous one. In the proposed scheme, the optimal maximum number of allowable HARQ transmissions and the optimal MCS (Modulation and Coding Scheme) level are determined for each packet to maximize the spectral efficiency. Our adopted approach exploits the channel diversity and increases the flexibility of the scheduling mechanism. Simulation results show that the proposed retransmission policy and link adaptation scheme increases the system performance in terms of spectral efficiency, while satisfying the latency and reliability constraints.

This paper characterizes the performance of interference alignment (IA) technique taking into account the dynamic traffic pattern and the probing/feedback cost. We consider a time-division duplex (TDD) system where transmitters acquire their channel state information (CSI) by decoding the pilot sequences sent by the receivers. Since global CSI knowledge is required for IA, the transmitters have also to exchange their estimated CSIs over a backhaul of limited capacity (i.e. imperfect case). Under this setting, we characterize in this paper the stability region of the system under both the imperfect and perfect (i.e. unlimited backhaul) cases, then we examine the gap between these two resulting regions.Further, under each case, we provide a centralized probing algorithm (policy) that achieves the max stability region. These stability regions and scheduling policies are given for the symmetric system where all the path loss coefficients are equal to each other, as well as for the general system. For the symmetric system, we compare the stability region of IA with the one achieved by a time division multiple access (TDMA) system where each transmitter applies a simple singular value decomposition technique (SVD). We then propose a scheduling policy that consists in switching between these two techniques, leading the system, under some conditions, to achieve a bigger stability region. Under the general system, the adopted scheduling policy is of a high computational complexity for moderate number of pairs, consequently we propose an approximate policy that has a reduced complexity but that achieves only a fraction of the system stability region. A characterization of this fraction is provided.