Stability Analysis of Frame Slotted Aloha Protocol

Frame Slotted Aloha (FSA) protocol has been widely applied in Radio Frequency Identification (RFID) systems as the de facto standard in tag identification. However, very limited work has been done on the stability of FSA despite its fundamental importance both on the theoretical characterisation of FSA performance and its effective operation in practical systems. In order to bridge this gap, we devote this paper to investigating the stability properties of FSA by focusing on two physical layer models of practical importance, the models with single packet reception and multipacket reception capabilities. Technically, we model the FSA system backlog as a Markov chain with its states being backlog size at the beginning of each frame. The objective is to analyze the ergodicity of the Markov chain and demonstrate its properties in different regions, particularly the instability region. By employing drift analysis, we obtain the closed-form conditions for the stability of FSA and show that the stability region is maximised when the frame length equals the backlog size in the single packet reception model and when the ratio of the backlog size to frame length equals in order of magnitude the maximum multipacket reception capacity in the multipacket reception model. Furthermore, to characterise system behavior in the instability region, we mathematically demonstrate the existence of transience of the backlog Markov chain.Comment: 14 pages, submitted to IEEE Transaction on Information Theor

KALOHA: ike i ke ALOHA

A new family of channel-access schemes  called KALOHA  (for ``Knowledge in ALOHA") is introduced.  KALOHA consists of modifying the pure ALOHA  protocol  by  endowing nodes with knowledge regarding the local times when packets  and acknowledgments are received,  and sharing  estimates of channel utilization at the medium access control (MAC) layer. The only physical-layer feedback needed   in KALOHA is the reception of  correct data packets and their ACKs. A  simple Markov-chain model is used  to  compare the throughput of KALOHA with ALOHA and slotted ALOHA. The analysis takes into account the amount of knowledge that nodes have and  the  effect of  acknowledgments and turnaround latencies.  The results  demonstrate the  benefits  derived from using  and sharing knowledge of channel utilization at the MAC layer.  KALOHA is more stable  than ALOHA and attains  more than double  the throughput of  ALOHA,  without the need for carrier sensing, requiring time slotting at the physical layer, or using other physical-layer mechanisms

Stability of synchronous queued RFID networks

Queued Radio Frequency Identification (RFID) networks arise naturally in many applications, where tags are grouped into batches, and each batch must be processed before the next reading job starts. In these cases, the system must be able to handle all incoming jobs, keeping the queue backlogs bounded. This property is called stability. Besides, in RFID networks, it is common that some readers cannot operate at the same time, due to mutual interferences. This fact reduces the maximum traffic that readers can process since they have to share the channel. Synchronous networks share the channel using a TDMA approach. The goal of this work is to analytically determine whether a synchronous queued RFID network attains stable operation under a given incoming traffic. Stability depends on the service rate, which is characterized in this paper using an exact numerical method based on a recursive analytical approach, overcoming the limitations of previous works, which were based on simplifications. We also address different flow optimization problems, such as computing the maximum joint traffic that a network can process stably, selecting the minimal number of readers to process a given total load, or determining the optimal timeslot duration, which are novel in the RFID literature.This work was supported by the Project AIM, (AEI/FEDER, EU) under Grant TEC2016-76465-C2-1-R

Stability of synchronous queued RFID networks

Queued Radio Frequency Identification (RFID) networks arise naturally in many applications, where tags are grouped into batches, and each batch must be processed before the next reading job starts. In these cases, the system must be able to handle all incoming jobs, keeping the queue backlogs bounded. This property is called stability. Besides, in RFID networks, it is common that some readers cannot operate at the same time, due to mutual interferences. This fact reduces the maximum traffic that readers can process since they have to share the channel. Synchronous networks share the channel using a TDMA approach. The goal of this work is to analytically determine whether a synchronous queued RFID network attains stable operation under a given incoming traffic. Stability depends on the service rate, which is characterized in this paper using an exact numerical method based on a recursive analytical approach, overcoming the limitations of previous works, which were based on simplifications. We also address different flow optimization problems, such as computing the maximum joint traffic that a network can process stably, selecting the minimal number of readers to process a given total load, or determining the optimal timeslot duration, which are novel in the RFID literature.Ministerio de Economía, Industria y Competitividad | Ref. TEC2016-76465-C2-1-

Multi-Agent DRL Approach for Energy-Efficient Resource Allocation in URLLC-Enabled Grant-Free NOMA Systems

peer reviewedGrant-free non-orthogonal multiple access (GF-NOMA) has emerged as a promising access technology for the fifth generation and beyond wireless networks that enable ultra-reliable and low-latency communications (URLLC) to ensure low access latency and high connectivity density. Furthermore, designing energy-efficient (EE) resource allocation strategies is a crucial aspect of future cellular system development. Taking these goals into account, this paper proposes an EE sub-channel and power allocation strategy for URLLC-enabled GF-NOMA (URLLC-GF-NOMA) systems based on multi-agent (MA) deep reinforcement learning (MADRL). In particular, the URLLC-GF-NOMA methods using MA dueling double deep Q network (MA3DQN), MA double deep Q network (MA2DQN), and MA deep Q network (MADQN) techniques are designed to enable users to select the most appropriate sub-channel and transmission power for their communications. The aim is to build an efficient MADRL-based solution, ensuring rapid convergence with small signaling overhead, to maximize the network EE while fulfilling the URLLC requirements of all users. Simulation results show that the MADQN and MA2DQN methods, which have lower complexity than MA3DQN, are more appropriate for the URLLC-GF-NOMA systems under consideration. Moreover, our proposed methods exhibit superior convergence characteristics, a reduction in signaling overhead, and enhanced EE performance compared to other benchmark strategies.FNR-funded project CORE 5G-Sky (Grant C19/IS/13713801

Stability Analysis of Frame Slotted Aloha Protocol

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Solutions for large scale, efficient, and secure Internet of Things

The design of a general architecture for the Internet of Things (IoT) is a complex task, due to the heterogeneity of devices, communication technologies, and applications that are part of such systems. Therefore, there are significant opportunities to improve the state of the art, whether to better the performance of the system, or to solve actual issues in current systems. This thesis focuses, in particular, on three aspects of the IoT. First, issues of cyber-physical systems are analysed. In these systems, IoT technologies are widely used to monitor, control, and act on physical entities. One of the most important issue in these scenarios are related to the communication layer, which must be characterized by high reliability, low latency, and high energy efficiency. Some solutions for the channel access scheme of such systems are proposed, each tailored to different specific scenarios. These solutions, which exploit the capabilities of state of the art radio transceivers, prove effective in improving the performance of the considered systems. Positioning services for cyber-physical systems are also investigated, in order to improve the accuracy of such services. Next, the focus moves to network and service optimization for traffic intensive applications, such as video streaming. This type of traffic is common amongst non-constrained devices, like smartphones and augmented/virtual reality headsets, which form an integral part of the IoT ecosystem. The proposed solutions are able to increase the video Quality of Experience while wasting less bandwidth than state of the art strategies. Finally, the security of IoT systems is investigated. While often overlooked, this aspect is fundamental to enable the ubiquitous deployment of IoT. Therefore, security issues of commonly used IoT protocols are presented, together with a proposal for an authentication mechanism based on physical channel features. This authentication strategy proved to be effective as a standalone mechanism or as an additional security layer to improve the security level of legacy systems