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Cedomir Stefanovic

Publications and source records attributed to Cedomir Stefanovic.

At least 55 records · Page 3Linked to original sources

Enabling LTE RACH Collision Multiplicity Detection via Machine Learning

The collision resolution mechanism in the Random Access Channel (RACH) procedure of the Long-Term Evolution (LTE) standard is known to represent a serious bottleneck in case of machine-type traffic. Its main drawbacks are seen in the facts that Base Stations (eNBs) typically cannot infer the number of collided User Equipments (UEs) and that collided UEs learn about the collision only implicitly, through the lack of the feedback in the later stage of the RACH procedure. The collided UEs then restart the procedure, thereby increasing the RACH load and making the system more prone to collisions. In this paper, we leverage machine learning techniques to design a system that outperforms the state-of-the-art schemes in preamble detection for the LTE RACH procedure. Most importantly, our scheme can also estimate the collision multiplicity, and thus gather information about how many devices chose the same preamble. This data can be used by the eNB to resolve collisions, increase the supported system load and reduce transmission latency. The presented approach is applicable to novel 3GPP standards that target massive IoT, e.g., LTE-M and NB-IoT.

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Sign-Compute-Resolve for Tree Splitting Random Access

We present a framework for random access that is based on three elements: physical-layer network coding (PLNC), signature codes and tree splitting. In presence of a collision, physical-layer network coding enables the receiver to decode, i.e. compute, the sum of the packets that were transmitted by the individual users. For each user, the packet consists of the user's signature, as well as the data that the user wants to communicate. As long as no more than K users collide, their identities can be recovered from the sum of their signatures. This framework for creating and transmitting packets can be used as a fundamental building block in random access algorithms, since it helps to deal efficiently with the uncertainty of the set of contending terminals. In this paper we show how to apply the framework in conjunction with a tree-splitting algorithm, which is required to deal with the case that more than K users collide. We demonstrate that our approach achieves throughput that tends to 1 rapidly as K increases. We also present results on net data-rate of the system, showing the impact of the overheads of the constituent elements of the proposed protocol. We compare the performance of our scheme with an upper bound that is obtained under the assumption that the active users are a priori known. Also, we consider an upper bound on the net data-rate for any PLNC based strategy in which one linear equation per slot is decoded. We show that already at modest packet lengths, the net data-rate of our scheme becomes close to the second upper bound, i.e. the overhead of the contention resolution algorithm and the signature codes vanishes.

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Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks

The fifth generation of cellular communication systems is foreseen to enable a multitude of new applications and use cases with very different requirements. A new 5G multiservice air interface needs to enhance broadband performance as well as provide new levels of reliability, latency and supported number of users. In this paper we focus on the massive Machine Type Communications (mMTC) service within a multi-service air interface. Specifically, we present an overview of different physical and medium access techniques to address the problem of a massive number of access attempts in mMTC and discuss the protocol performance of these solutions in a common evaluation framework.

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Decentralized DC MicroGrid Monitoring and Optimization via Primary Control Perturbations

We treat the emerging power systems with direct current (DC) MicroGrids, characterized with high penetration of power electronic converters. We rely on the power electronics to propose a decentralized solution for autonomous learning of and adaptation to the operating conditions of the DC Mirogrids; the goal is to eliminate the need to rely on an external communication system for such purpose. The solution works within the primary droop control loops and uses only local bus voltage measurements. Each controller is able to estimate (i) the generation capacities of power sources, (ii) the load demands, and (iii) the conductances of the distribution lines. To define a well-conditioned estimation problem, we employ decentralized strategy where the primary droop controllers temporarily switch between operating points in a coordinated manner, following amplitude-modulated training sequences. We study the use of the estimator in a decentralized solution of the Optimal Economic Dispatch problem. The evaluations confirm the usefulness of the proposed solution for autonomous MicroGrid operation.

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Reliable Video Streaming over mmWave with Multi Connectivity and Network Coding

The next generation of multimedia applications will require the telecommunication networks to support a higher bitrate than today, in order to deliver virtual reality and ultra-high quality video content to the users. Most of the video content will be accessed from mobile devices, prompting the provision of very high data rates by next generation (5G) cellular networks. A possible enabler in this regard is communication at mmWave frequencies, given the vast amount of available spectrum that can be allocated to mobile users; however, the harsh propagation environment at such high frequencies makes it hard to provide a reliable service. This paper presents a reliable video streaming architecture for mmWave networks, based on multi connectivity and network coding, and evaluates its performance using a novel combination of the ns-3 mmWave module, real video traces and the network coding library Kodo. The results show that it is indeed possible to reliably stream video over cellular mmWave links, while the combination of multi connectivity and network coding can support high video quality with low latency.

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On the Modeling and Performance Assessment of Random Access with SIC

In this paper, we review the key figures of merit to assess the performance of advanced random access (RA) schemes exploiting physical layer coding, repetitions and collision resolution techniques. We then investigate RA modeling aspects and their impact on the figures of merit for the exemplary advanced RA schemes: Contention Resolution Diversity Slotted ALOHA (CRDSA), Irregular Repetition Slotted ALOHA (IRSA), Coded Slotted ALOHA (CSA) and Enhanced Spread-Spectrum ALOHA (E-SSA). We show that typical simplifications of the reception model when used to optimize RA schemes lead to inaccurate findings, both in terms of parameter optimization and figures of merit, such as the packet loss ratio (PLR) and throughput. We also derive a generic RA energy efficiency model able to compare the schemes in terms of the energy required to transmit a packet. The combination of achievable RA throughput at the target PLR and energy efficiency, for the same average user power investment per frame and occupied bandwidth, shows that E-SSA, which is an unslotted scheme, provides the best overall performance, while, in terms of the slotted schemes, CRDSA outperforms the more elaborated IRSA and CSA. This surprising results is due to the fact that the IRSA and CSA optimization has so far been performed using RA channel models that are not accurately reflecting the physical layer receiver behavior. We conclude by providing insights on how to include more accurate reception models in the IRSA and CSA design and optimization.

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Wireless Access for Ultra-Reliable Low-Latency Communication (URLLC): Principles and Building Blocks

Ultra-reliable low latency communication (URLLC) is an important new feature brought by 5G, with a potential to support a vast set of applications that rely on mission-critical links. In this article, we first discuss the principles for supporting URLLC from the perspective of the traditional assumptions and models applied in communication/information theory. We then discuss how these principles are applied in various elements of the system design, such as use of various diversity sources, design of packets and access protocols. The important messages are that there is a need to optimize the transmission of signaling information, as well as a need for a lean use of various sources of diversity.

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Asymptotic Performance of Coded Slotted ALOHA with Multi Packet Reception

In this letter, we develop a converse bound on the asymptotic load threshold of coded slotted ALOHA (CSA) schemes with K-multi packet reception capabilities at the receiver. Density evolution is used to track the average probability of packet segment loss and an area matching condition is applied to obtain the converse. For any given CSA rate, the converse normalized to K increases with K, which is in contrast with the results obtained so far for slotted ALOHA schemes based on successive interference cancellation. We show how the derived bound can be approached using spatially-coupled CSA.

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Frameless ALOHA with Reliability-Latency Guarantees

One of the novelties brought by 5G is that wireless system design has increasingly turned its focus on guaranteeing reliability and latency. This shifts the design objective of random access protocols from throughput optimization towards constraints based on reliability and latency. For this purpose, we use frameless ALOHA, which relies on successive interference cancellation (SIC), and derive its exact finite-length analysis of the statistics of the unresolved users (reliability) as a function of the contention period length (latency). The presented analysis can be used to derive the reliability-latency guarantees. We also optimize the scheme parameters in order to maximize the reliability within a given latency. Our approach represents an important step towards the general area of design and analysis of access protocols with reliability-latency guarantees.

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Grant-Free Radio Access for Short-Packet Communications over 5G Networks

Radio access management plays a vital role in delay and energy consumption of connected devices. The radio access in existing cellular networks is unable to efficiently support massive connectivity, due to its signaling overhead. In this paper, we investigate an asynchronous grant-free narrowband data transmission protocol that aims to provide low energy consumption and delay, by relaxing the synchronization/reservation requirement at the cost of sending several packet copies at the transmitter side and more complex signal processing at the receiver side. Specifically, the timing and frequency offsets, as well as sending of multiple replicas of the same packet, are exploited as form of diversities at the receiver-side to trigger successive interference cancellation. The proposed scheme is investigated by deriving closed-form expressions for key performance indicators, including reliability and battery-lifetime. The performance evaluation indicates that the scheme can be tuned to realize long battery lifetime radio access for low-complexity devices. The obtained results indicate existence of traffic load regions, where synchronous access outperforms asynchronous access and vice versa.

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Small-Signal Analysis of the Microgrid Secondary Control Considering a Communication Time Delay

This paper presents a small-signal analysis of an islanded microgrid composed of two or more voltage source inverters connected in parallel. The primary control of each inverter is integrated through internal current and voltage loops using PR compensators, a virtual impedance, and an external power controller based on frequency and voltage droops. The frequency restoration function is implemented at the secondary control level, which executes a consensus algorithm that consists of a load-frequency control and a single time delay communication network. The consensus network consists of a time-invariant directed graph and the output power of each inverter is the information shared among the units, which is affected by the time delay. The proposed small-signal model is validated through simulation results and experimental results. A root locus analysis is presented that shows the behavior of the system considering control parameters and time delay variation.

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Coded Random Access: Applying Codes on Graphs to Design Random Access Protocols

The rise of machine-to-machine communications has rekindled the interest in random access protocols as a support for a massive number of uncoordinatedly transmitting devices. The legacy ALOHA approach is developed under a collision model, where slots containing collided packets are considered as waste. However, if the common receiver (e.g., base station) is capable to store the collision slots and use them in a transmission recovery process based on successive interference cancellation, the design space for access protocols is radically expanded. We present the paradigm of coded random access, in which the structure of the access protocol can be mapped to a structure of an erasure-correcting code defined on graph. This opens the possibility to use coding theory and tools for designing efficient random access protocols, offering markedly better performance than ALOHA. Several instances of coded random access protocols are described, as well as a case study on how to upgrade a legacy ALOHA system using the ideas of coded random access.

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User Activity Detection in Massive Random Access: Compressed Sensing vs. Coded Slotted ALOHA

Machine-type communication services in mobile cel- lular systems are currently evolving with an aim to efficiently address a massive-scale user access to the system. One of the key problems in this respect is to efficiently identify active users in order to allocate them resources for the subsequent transmissions. In this paper, we examine two recently suggested approaches for user activity detection: compressed-sensing (CS) and coded slotted ALOHA (CSA), and provide their comparison in terms of performance vs resource utilization. Our preliminary results show that CS-based approach is able to provide the target user activity detection performance with less overall system resource utilization. However, this comes at a price of lower energy- efficiency per user, as compared to CSA-based approach.

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Irregular Repetition Slotted ALOHA over the Rayleigh Block Fading Channel with Capture

Random access protocols relying on the transmission of packet replicas in multiple slots and exploiting interference cancellation at the receiver have been shown to achieve per- formance competitive with that of orthogonal schemes. So far the optimization of the repetition degree profile, defining the probability for a user to transmit a given number of replicas, has mainly been performed targeting the collision channel model. In this paper the analysis is extended to a block fading channel model, also assuming capture effect at the receiver. Density evolution equations are developed for the new setting and, based on them, some repetition degree profiles are optimized and analyzed via Monte Carlo simulation in a finite frame length setting. The derived distributions are shown to achieve throughputs largely exceeding 1 [packet/slot].

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A Pseudo-Bayesian Approach to Sign-Compute-Resolve Slotted ALOHA

Access reservation based on slotted ALOHA is commonly used in wireless cellular access. In this paper we investigate its enhancement based on the use of physical-layer network coding and signature coding, whose main feature is enabling simultaneous resolution of up to K users contending for access, where K >= 1. We optimise the slot access probability such that the expected throughput is maximised. In particular, the slot access probability is chosen in line with an estimate of the number of users in the system that is obtained relying on the pseudo-Bayesian approach by Rivest, which we generalise for the case that K > 1. Under the assumption that this estimate reflects the actual number of users, we show that our approach achieves throughput 1 in the limit of large K.

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Minimizing Data Distortion of Periodically Reporting IoT Devices with Energy Harvesting

Energy harvesting is a promising technology for the Internet of Things (IoT) towards the goal of self-sustainability of the involved devices. However, the intermittent and unreliable nature of the harvested energy demands an intelligent management of devices' operation in order to ensure a sustained performance of the IoT application. In this work, we address the problem of maximizing the quality of the reported data under the constraints of energy harvesting, energy consumption and communication channel impairments. Specifically, we propose an energy-aware joint source-channel coding scheme that minimizes the expected data distortion, for realistic models of energy generation and of the energy spent by the device to process the data, when the communication is performed over a Rayleigh fading channel. The performance of the scheme is optimized by means of a Markov Decision Process framework.

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Reliable and Efficient Access for Alarm-initiated and Regular M2M Traffic in IEEE 802.11ah Systems

EEE 802.11ah is a novel WiFi-based protocol, aiming to provide an access solution for the machine-to-machine (M2M) communications. In this paper, we propose an adaptive access mechanism that can be seamlessly incorporated into IEEE 802.11ah protocol operation and that supports all potential M2M reporting regimes, which are periodic, on-demand We show that it is possible to both efficiently and reliably resolve all reporting stations in the cell, within the limits of the allowed deadlines. As a side result, we also provide a rationale for modeling the inter-arrival time in alarm events by using the Beta distribution, a model that is considered in the 3GPP standardization.

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Compressive Coded Random Access for Massive MTC Traffic in 5G Systems

Massive MTC support is an important future market segment, but not yet efficiently supported in cellular systems. In this paper we follow-up on recent concepts combining advanced MAC protocols with Compressed Sensing (CS) based multiuser detection. Specifically, we introduce a concept for sparse joint activity, channel and data detection in the context of the Coded ALOHA (FDMA) protocol. We will argue that a simple sparse activity and data detection is not sufficient (as many papers do) because control resources are in the order of the data. In addition, we will improve on the performance of such protocols in terms of the reduction of resources required for the user activity, channel estimation and data detection. We will mathematically analyze the system accordingly and provide expressions for the capture probabilities of the underlying sparse multiuser detector. Finally, we will provide structured CS algorithms for the joint estimation scheme and evaluate its performance.

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