Number Of Time Slots Research Articles

A Simple Time–Space Diversity Scheme Using Extended Shaping Pulse

This paper proposes a new time–space diversity scheme for data transmission through flat fading channels. Extended pulses are used to shape the modulated symbols at different time slots. The proposed transmitter does not change the transmission rate of the modulated symbols after the shaping process. One transmitting antenna is used to transmit the shaped symbols. Multiple antennas are used in the receiver to collect the transmitted symbols. The diversity gain in the proposed system is the product of the numbers of time slots through which the modulated symbol is transmitted and the number of receiving antennas. The proposed transmitter uses neither space–time codes nor spreading codes. The received signal suffers from intentional inter-symbol interference due to the correlation between the shaped symbols. Instead of using equalizers to remove this interference, multi-symbols detectors are used to exploit this interference to achieve the desired diversity gain. Buffers store the replicas of the desired symbol after the multi-symbols detector during its diverse period. Two-dimensional maximal ratio combiner adds these replicas in one decision variable. The proposed system achieves high diversity gain in flat fading channels with one transmitting antenna, and without affecting the used communication resources.

Fast node cardinality estimation and cognitive MAC protocol design for heterogeneous machine-to-machine networks

Machine-to-Machine (M2M) networks are an emerging technology with applications in numerous areas including smart grids, smart cities, vehicular telematics, and healthcare. In this paper, we design two estimation protocols for rapidly obtaining separate estimates of the number of active nodes of each traffic type in a heterogeneous M2M network with $T$ types of M2M nodes (e.g., those that send emergency, periodic, normal type data etc), where $T \geq 2$ is an arbitrary integer. One of these protocols, Method I, is a simple scheme, and the other, Method II, is more sophisticated and performs better than Method I. Also, we design a medium access control (MAC) protocol that supports multi-channel operation for a heterogeneous M2M network with an arbitrary number of types of M2M nodes, operating as a secondary network using Cognitive Radio technology. Our Cognitive MAC protocol uses the proposed node cardinality estimation protocols to rapidly estimate the number of active nodes of each type in every time frame; these estimates are used to find the optimal contention probabilities to be used in the MAC protocol. We compute a closed form expression for the expected number of time slots required by Method I to execute as well as a simple upper bound on it. Also, we mathematically analyze the performance of the Cognitive MAC protocol and obtain expressions for the expected number of successful contentions per frame and the expected amount of energy consumed. Finally, we evaluate the performances of our proposed estimation protocols and Cognitive MAC protocol using simulations.

A novel approach of dynamic base station switching strategy based on Markov decision process for interference alignment in VANETs

In Vehicular Ad-hoc Networks (VANETs), high frequent interaction of safety-related information is required among vehicles and imposes urgent demand on information update. In order to reduce communication delay and improve the capacity of concurrent communication, in this paper we propose that the multi-antenna vehicle could takeover the channel management as dynamic base station to apply Multiple-Input Multiple-Output communication and interference management approach in Vehicle to Vehicle (V2V) communications. Firstly, we construct an Markov decision process (MDP) model for multi-antenna vehicle to estimate whether it is appropriate to be dynamic base station. In addiction, Monte Carlo Tree Search algorithm is introduced to derive MDP policy. Thirdly, the V2V Interference Alignment (V2V-IA) model is constructed for dynamic base station to obtain IA scheme to manage V2V communications and IA in VANETs. To achieve the goal of improving frequency of information update, we propose an optimized problem to minimize total number of time slots, which is required for completing global safety-related information delivery. Simulation results show that the frequency of information update can be improved effectively by the proposed approach and the average improvement could go up to 40%.

Multi-Hop LoRa Network Protocol with Minimized Latency

LoRa (Long Range) is a long-range communications capacity with chirp spread spectrum modulation. It has been developed for Internet of Things (IoT) applications for long-distance and low power consumption. Some authors proposed LoRa protocols such as LoRaWAN, LoRaBlink, DQ-LoRa and the multi-hop LoRa network with linear topology; however, these protocols have disadvantages. In this paper, we propose a minimized latency multi-hop LoRa network protocol that is collision-free with low latency to improve on the disadvantages. First, in the proposed protocol, tree topology is constructed by exchanging packets between LoRa nodes and the sink node. During this period, a timeslot and channel are assigned to each tree link, over which LoRa nodes communicate with their parent node and which is collision-free with its neighbor nodes. After the tree construction period, LoRa nodes start data transmission using the timeslot and channel that they have already been assigned to in the tree construction period. We developed the proposed protocol in a LoRa node prototype using the MultiTech mDot module, and we conducted experiments at Ulsan University. The results show that the proposed protocol provides high reliability, parallel transmissions, a minimized number of timeslots assigned for all the links in the network, a minimized packet size, and low latency.

A distributed algorithm for vertex coloring problems in wireless networks

Abstract A lot of problems in computer networks are modeled by the vertex coloring problem (VCP), the multicoloring problem (MCP), the bandwidth coloring problem (BCP), and the bandwidth multicoloring problem (BMCP). To solve the VCP with Δ + 1 colors, a myriad distributed algorithms have been proposed to reduce time complexity (the number of rounds), where Δ is the maximum vertex degree in the graph. Time and communication complexities of these algorithms are functions of n and Δ , where n is the number of vertices in the graph. The MCP can be converted into VCP after transformation of the graph; the transformation increases the time and communication complexities. However, no distributed algorithms for BCP and BMCP have been proposed in the literature. In this paper, we propose a General Distributed Vertex Coloring Algorithm (GDVCA) to solve four problems in wireless networks. In GDVCA, some (and not necessarily all) vertices assign colors to themselves and their neighbors, which we refer to them as assigning vertices. The communication cost of GDVCA is very low; the number of messages transmitted by each assigning vertex is one and by the other vertices is zero. Assigning vertices assign the first available colors to uncolored vertices; moreover assigning vertices can use heuristic methods to choose the next proper vertex for coloring. Therefore, the number of colors used by the distributed algorithm GDVCA is significantly low. The number of time slots required to color a graph is O ( Δ 2 ) and at most n, where each round comprises several time slots.

Cognitive Networks With In-Band Full-Duplex Radios: Jamming Attacks and Countermeasures

Although in-band full-duplex (IBFD) radios promise to double the throughput of a wireless link, they are more vulnerable to jamming attacks than their out-of-band full-duplex (OBFD) counterparts. For two communicating OBFD nodes, a jammer needs to attack both the uplink and the downlink channels to completely break the communication link. In contrast, only one common channel needs to be jammed in the case of two IBFD nodes. Even worse, a jammer with self-interference suppression (SIS) capabilities (the underlying technique of IBFD radios) can learn the transmitters' activity while injecting interference, allowing it to react instantly to the transmitter's strategies. In this work, we consider a power-constrained IBFD “reactive-sweep” jammer that sweeps through the set of channels by jamming a subset of them simultaneously. We model the interactions between the IBFD radios and the jammer as a stochastic constrained zero-sum Markov game in which nodes adopt the frequency hopping (FH) technique as their strategies to counter jamming attacks. Beside the IBFD transmission-reception (TR) mode, we introduce an additional operation mode, called transmission-detection (TD), in which an IBFD radio transmits and leverages its SIS capability to detect jammers. The aim of the TD mode is to make IBFD radios more cognitive to jamming. The nodes' optimal defense strategy that guides them when to hop and which operational mode (TD or TR) to use is then established from the equilibrium of the stochastic Markov game. We prove that this optimal policy has a threshold structure, in which IBFD nodes stay on the same channel up to a certain number of time slots before hopping. Simulation results show that our policy significantly improves the throughput of IBFD nodes under jamming attacks.

Evolutionary computing approach to optimize superframe scheduling on industrial wireless sensor networks

The industrial wireless sensor domain has undergone a shift in paradigm as a consequence of Internet of Things (IoT), a thriving technology that has been leading the way in short-range and fixed wireless sensing. One of the problems associated with industrial wireless sensor networks (IWSNs) is finding the optimal solution for minimizing defect time in superframe scheduling. This paper proposed a method based on the use of evolutionary algorithms, namely particle swarm optimization (PSO), orthogonal learning PSO, genetic algorithm (GA), and modified GA for optimizing the superframe scheduling. Additionally, we evaluated a contemporary method, deadline monotonic scheduling, on the ISA 100.11a protocol. The use of this standard as a case study means that the presented 72 simulations are object-oriented, with numerous variations in the number of timeslots and wireless sensor nodes. The simulation results show that the use of GA and modified GA can improve the performance in terms of idle, missed deadlines, memory consumption, and processing time comparing to other metaheuristic algorithms. A comprehensive analysis and detailed performance evaluation are provided in the paper.

Kalman Filtering Based Adaptive Transfer in Energy Harvesting IoT Networks

In this paper, we investigate an energy prediction algorithm based on Kalman filtering in energy harvesting IoT networks. The IoT nodes harvest renewable energy from nature and powered by green energy only. Owing to the space-time instability and non-uniformity of renewable energy, the IoT nodes may have insufficient energy supply. An unresolved challenge is accurately predicting the available renewable energy, and developing low complexity solutions that incorporate a lossless transfer guarantee. With this in mind, we propose the energy prediction algorithm based on Kalman filtering to bridge the gap between lossless transfer and unstable renewable energy. The energy prediction is performed at the access point in order to dynamically adjust the number of bits to be sent, and the data loss due to receiver energy depletion will be improved. In addition, real solar and wind energy profiles are exploited by simulations. The simulation results show that the proposed energy prediction algorithm can improve transmission efficiency in terms of the rate of drop bits and the number of time slots needed to transmit a given payload, and reduce the wastes of harvested renewable energy.

Adaptive Resource Allocation Method Based on Deep Q Network for Industrial Internet of Things

The transformation and upgrading of the industrial manufacturing field brings important development opportunities for the promotion and deployment of the Industrial Internet of Things (IIoT). How to connect huge number of IIoT nodes to the current IP-based Internet for promoting the integration of industrialization and informationization is a key issue towards IIoT. Targeting at the insufficiency that existing algorithms only support a single channel and utilize limited number of time slots, which results in the deteriorated performance for solving the problem of resource allocation for nodes with different priorities. In this paper the self-similarity of the observation data of the IIoT nodes is evaluated to dynamically prioritize the nodes, and then Deep Q Network (DQN) algorithm is adopted to design an adaptive resource allocation method that takes into account the characteristics of diverse node priorities. Simulation results demonstrate that the proposed method can effectively improve network throughput and reduce data transmission delay in comparison with existing methods.

Number of subcarrier filter coefficients in GFDM system: effect on performance

Generalized Frequency Division Multiplexing (GFDM) is a non-orthogonal multicarrier transmission scheme proposed for fifth (5G) and future generation wireless networks. Due to its attractive properties, it has been recently discussed as a candidate waveform for the future wireless communication systems. GFDM is introduced as a generalized form of the widely used Orthogonal Frequency Division Multiplexing (OFDM) modulation scheme and it uses only one cyclic prefix (CP) for a group of symbols. The main focus of this work is to present like impact on the system performance the coefficient quantity of the subcarrier filter. A simple method for the computation of the coefficients of the prototype filter is employed. Besides, it is presented a structure for the GFDM by taking advantage of the arrangement in the modulation matrix. We evaluated the Bit Error Rate (BER) using the receiver models presented in this work. The results showed that the BER is affected according to the coefficients quantity of the prototype filter. Based on the obtained results, the coefficients quantity has a relation with the number of time slots of the GFDM system.

Uniquely Decodable Codes for Physical-Layer Network Coding in Wireless Cooperative Communications

Physical-layer network coding (PNC) has received much attention, both from academia and industry lately, since it takes advantages of multiple-access signals. Because of a reduced number of time slots (TSs), PNC is capable of improving throughput significantly, especially for a typical 3-node network consisting of 2 user terminals and 1 relay node. However, a network with $M$ nodes ( $M>3$ ) and without adopting additional techniques needs $(2M-2)$ TSs to realize information exchange among all the nodes, since network coding is unable to distinguish between users at the relay node. This paper proposes uniquely decodable codes (UDCs) for PNC in wireless cooperative communications. The proposed UDC requires only two TSs for information exchange irrespective of the number of nodes in the network. This paper also investigates the amplify-and-forward and decode-and-forward modes for UDC-based PNC. The bit error rate and throughput of the proposed schemes are analyzed in this paper. Using simulation results, we demonstrate that our theoretical results align well with the simulation results.

Cooperative Time Successive SSK-M-ary Modulation for Decode-and-Forward Relay Systems

Space shift keying (SSK) is a single radio frequency (RF) chain multiple-input multiple-output (MIMO) scheme that uses the index of transmit antennas for information transmission. Time successive SSK- $ M$ -ary modulation (TSSM) and multi RF chain TSSM (MRF-TSSM) are recent MIMO techniques that achieve second order transmit diversity. We propose two cooperative relaying systems to attain distributed diversity in addition to transmit diversity of TSSM and MRF-TSSM. Cooperative-TSSM-1 (Coop-TSSM-1) uses multibranch relaying where TSSM is used in orthogonal time slots during the cooperative phase. Coop-TSSM-2 maps symbols to lower order constellations at multiple relays for simultaneous transmission of information using MRF-TSSM. We consider Decode-and-forward (DF) relaying where relays that correctly detect symbols forward it. We analyze the average number of relays that participate in cooperation, the end-to-end performance using a tight upper bound on the bit error rate (BER) and the asymptotic BER expressions to analyze diversity orders of both cooperative systems. We validate all analyzes using simulation results. From the analysis and results we show that Coop-TSSM-1 achieves better diversity order compared to Coop-TSSM-2 at the cost of higher number of time slots for completing the cooperative phase. Further in Coop-TSSM-2, results indicate that different constellation mappings used in MRF-TSSM during cooperative phase impact the BER performance. By applying spatial modulation based transmit diversity and $M$ -ary Modulation systems in the cooperative setups of Coop-TSSM schemes, performance comparison is given which highlights the significance of Coop-TSSM schemes.

An Analytical Model for Interference Alignment in Broadcast Assisted VANETs.

Application of safety-related information interaction among vehicles has always been a research frontier in Vehicular Ad-hoc NETworks (VANETs). These messages require high real-time performance. There is a lot of research dependant on creating optimization model for communication task scheduling or routing protocols to reduce communication delay. In this paper, we analyze characteristics of safety-related information and introduce Interference Alignment (IA) technology in VANETs. To further improve routing efficiency, a data-driven assisted transmission routing and broadcast model framework for Vehicle to Vehicle(V2V) and Vehicle to Infrastructure (V2I) communication are constructed which are the basis for IA. Depending on the proposed model, we propose an optimization problem of minimizing total number of time slots required for safety information sharing in VANETs. Then a clustering algorithm is designed to narrow feasible solution space. Simulation results show that the approach can effectively reduce the number of time slots required and improve link use by 20% percent compared with no IA applied.

Semi-Blind Detection in Hybrid Massive MIMO Systems via Low-Rank Matrix Completion

In massive multiple-input multiple-output (MIMO) systems with hybrid analog/digital architectures, large training overhead is required for conventional pilot-only methods to estimate channel accurately before detecting data. To reduce the training overhead, a semi-blind detection method is proposed for data detection without knowing channel in an uplink multi-user system. The main idea is to exploit the received signal corresponding to both the pilot and data payload for channel estimation or data detection via a low-rank matrix completion formulation. The leveraged low-rank property stems from the fact that the number of active users $K$ is typically much smaller than the number of antennas $N_{a}$ at a base station and the number of time slots $T_{c}$ in a coherence interval. Compared with the pilot-only method, the number of pilots required is reduced from an order of $N_{a}$ to $K$ . Two iterative algorithms are introduced to solve the low-rank matrix completion problem: regularized alternating least squares and bilinear generalized approximate message passing. We further extend the semi-blind detection method to systems with low-resolution analog-to-digital converters. Simulation results show that the proposed methods achieve significant performance gain over the pilot-only method with reduced training overhead for hybrid massive MIMO systems in various settings.

An Energy-efficient Distributed TDMA Scheduling Algorithm for ZigBee-like Cluster-tree WSNs

The design of Medium Access Control (MAC) protocol for Wireless Sensor Networks (WSNs) with both limited energy consumption and data delivery time is crucial for industrial and control applications. Since Time Division Multiple Access (TDMA) MAC eliminates the collision occurrence and seeks the minimization of the number of time-slots assigned to each node, the energy consumption of the nodes is reduced. Furthermore, with the proper allocation of the time-slots to the nodes, the transmission delay can be significantly reduced. In this article, we propose TDMA scheduling algorithm for Cluster-tree topology WSNs that meets the timeliness and the energy demands. The algorithm adopts an elegant approach that expresses the timing constraints of the data transmissions as an integer multiple of the length of the schedule period. Moreover, since the distributed algorithm is well-suited to the scarce resources of the WSNs, we focus on the distributed methods that allow each cluster to come up with its allocated time-slots. The algorithm is based on graph theory, such as distributed shortest path, distributed topological ordering, and distributed graph coloring algorithms. The efficiency of the algorithm, regarding the elapsed time to construct the schedule and the energy consumption, is evaluated over benchmark instances up to several thousands of nodes.

Performance Comparison between Fountain Codes-Based Secure MIMO Protocols with and without Using Non-Orthogonal Multiple Access

In this paper, we propose and evaluate the performance of fountain codes (FCs) based secure transmission protocols in multiple-input-multiple-output (MIMO) wireless systems, in presence of a passive eavesdropper. In the proposed protocols, a source selects its best antenna to transmit fountain encoded packets to a destination that employs selection combining (SC) or maximal ratio combing (MRC) to enhance reliability of the decoding. The transmission is terminated when the destination has a required number of the encoded packets to reconstruct the original data of the source. Similarly, the eavesdropper also has the ability to recover the source data if it can intercept a sufficient number of the encoded packets. To reduce the number of time slots used, the source can employ non-orthogonal multiple access (NOMA) to send two encoded packets to the destination at each time slot. For performance analysis, exact formulas of average number of time slots (TS) and intercept probability (IP) over Rayleigh fading channel are derived and then verified by Monte-Carlo simulations. The results presented that the protocol using NOMA not only reduces TS but also obtains lower IP at medium and high transmit signal-to-noise ratios (SNRs), as compared with the corresponding protocol without using NOMA.

FWB: Funneling Wider Bandwidth algorithm for high performance data collection in Wireless Sensor Networks

Many Wireless Sensor Networks (WSNs) applications demand to collect large volumes of data in a coordinated approach. To do this, a many-to-one pattern (convergecast) communication in tree-based WSN is used, but traffic near the sink node commonly becomes the network bottleneck. Thus, we propose an extension to a wireless network standard to provide wider bandwidth channels. We explore how fast the information can be collected in a WSN organized as a tree, with the radios operating with these wider bandwidth channels. As consequence, we proposed and implemented Funneling Wider Bandwidth (FWB), an algorithm that minimizes schedule length in networks with radios operating with the proposed extension. We proved that the algorithm is optimal in calculating a minimum number of time slots. In this way, we obtain a higher average throughput and a lesser number of time slots. Results from simulations and experiments on a real testbed confirm these gains. The proposed approach could be adapted and used with other related standards such as WirelessHARTTM, ISA 100.11a and IEEE 802.15.4e TSCH. Experiment results showed that with this wider bandwidth emulated in a given topology, the packets received per second by the sink node increased by 122.8% in comparison with just one bandwidth.

User Behavior Driven MAC Scheduling for Body Sensor Networks: A Cross-Layer Approach

In deploying body sensor networks (BSNs), sampling rates might be dynamically tuned to fit application requirements (e.g., monitoring patients’ different activities), which helps conserving energy for battery-powered sensors. However, this results in variable data rates among sensors, which further requires an efficient resource allocation to maintain reliable transmission accommodating all traffic loads. We thereby address this joint problem of transmission reliability and energy efficiency by proposing a BSN system that autonomously detects user behaviors, which, in turn, trigger dynamic sampling and resource scheduling via an adaptive MAC scheduling scheme. This cross-layer scheme uses time-slotted channel hopping (TSCH) in IEEE 802.15.4, which is a reliable low-power MAC protocol. Specifically, the proposed solution determines the best TSCH slotframe length for specific application requirements and the number of timeslots to be added/removed according to dynamic sampling rates, and then allocates timeslots via an equally spaced timeslot allocation algorithm. We implement our proposed approach on a BSN testbed, which features both state-of-the-art hardware and software architectures. The experimental results are conducted to evaluate our proposed solution in terms of throughput, packet delivery ratio, and energy per bit, which demonstrates that our cross-layer solution ensures reliable data transmission and energy efficiency compared to existing techniques.

New selectors and locally thin families with applications to multi-access channels supporting simultaneous transmissions

We consider the Conflict Resolution Problem in the context of a multiple-access system in which several stations can transmit their messages with success simultaneously. We assume that there are n stations and at most k, k≤n, stations are active at the same time, i.e., are willing to transmit a message. If at most d, d≤k, active stations transmit simultaneously then their messages are successfully transmitted, whereas if more than d active stations transmit simultaneously then their messages are lost. The active stations receive a feedback from the channel that informs them on whether their messages have been successfully transmitted. The measure to optimize is the number of time slots needed to solve conflicts among all active stations, i.e., to make all active stations transmit their messages successfully. We prove that this measure decreases with the number d of messages that can be simultaneously transmitted with success by presenting a conflict resolution algorithm that uses a 1/d ratio of the number of time slots used by the optimal conflict resolution algorithm for the particular case d=1[26]. We give a lower bound which is only a log⁡(k/d) factor away from the number of time slots used by the algorithm. The algorithm is obtained via a new kind of the selectors of [13], whereas the lower bound is implied by a non-existential result for a new generalization of the locally thin families of [1,12]. We present also a randomized algorithm that allows to generate the above combinatorial structures in expected polynomial time when k=O(1).

Penjadwalan Perkuliahan dengan Metode Metaheuristic Ant Colony Optimization Studi Kasus Politeknik Negeri Bali

Lecture scheduling problems are a very complex problem, where the core of the scheduling is how to schedule several components consisting of students, lecturers, space, time, and subject matter with due regard to certain constraints and constraints. The goal to be achieved is to apply the Ant Colony Optimization (ACO) Metaheuristic method to optimize the lecture scheduling system. Every step taken by ACO uses an algorithm adapted from ant behavior to solve combinatorial problems. This system is created using Microsoft Visual Basic programming by entering several parameters, namely Lecturer, Course, Room, and several variables from each parameter which are then processed to produce lecture scheduling. The results obtained from the ACO implementation to solve college scheduling problems are seen from the number of constrained constraints and the length of time required from each iteration in each method to get a class schedule so that they get a schedule with a 82 percent truth level which is a comparison of constraint violations to the total number of timeslot used for scheduling.