Multiple Time Slots Research Articles

ConvAE-Advanced: Adaptive Transmission Across Multiple Timeslots for Error Resilient Operation

Recent advancements in machine learning for communications show that channel autoencoders could revolutionize conventional communication systems through end-to-end optimization. For channel autoencoders to reliably transmit over the air, a scheme to enable adaptive use of resources is needed. Thus, we propose ConvAE-Advanced, an improved channel autoencoder structure that can adaptively transmit across multiple timeslots. ConvAE-Advanced utilizes an unexploited input dimension in ConvAE by the use of the resource-aware residual block and whole resource power normalization. This enabled ConvAE-Advanced to adaptively transmit information according to channel conditions. Simulations for a 2-by-2 multiple-input multiple-output system under the WINNER2 A1 scenario shows that ConvAE-Advanced outperforms ConvAE across all SNR ranges. Most importantly, ConvAE-Advanced can achieve a better BER and achievable rate performance without additional wireless resource usage compared to ConvAE.

Understanding Cooperative Data Exchange Problem in Multi-Hop Wireless Network

This letter theoretically formulates the coded cooperative data exchange (CCDE) problem in multi-channel multi-hop wireless networks, where a set of nodes initially hold a subset of packets and wish to retrieve all desired packets via multi-hop wireless communication. At first, we propose the model of tentative transmission, with which we can jointly consider resource allocation, transmission scheduling, and transmitted packet scheduling. Then, based on the time expanded graph, we convert the CCDE problem in multiple time slots into a single source and multiple sinks network (SSMN) within a time slot. Finally, the relationship between the required time slots and the number of channels is theoretically formulated based on the constructed SSMN. Experiments demonstrate that the gain due to the increasing number of channels flattens.

Joint Antenna Detection and Bayesian Channel Estimation for Non-Coherent User Terminals

In this paper, we propose a method of improving the channel estimates for non-coherent multi-antenna terminals, which are terminals that cannot control the relative phase between its antenna ports, with channels that can be considered constant over multiple time slots. The terminals have multiple antennas and are free to choose whichever antenna they want to use in each time slot. An unknown phase shift is introduced in each time slot as we cannot guarantee that the terminals are phase coherent across time slots. We compare three different clustering techniques that we use to detect the active antenna. We also compare a set of different statistical and heuristic estimators for the channels and the phase shifts. We evaluate the methods by using correlated Rayleigh fading and three different bounds on the uplink capacity. The accuracy of the capacity bounds are verified with bit-error-rate simulations. With our proposed methods we can have an SNR improvement of approximately 2 dB at 1 bit/s/Hz.

Jamming-Resilient Frequency Hopping-Aided Secure Communication for Internet-of-Things in the Presence of an Untrusted Relay

In this paper, we propose a light-weight jamming-resistant scheme for the Internet-of-Things (IoT) in 5G networks to ensure high-quality communication in a two-hop cooperative network. In the considered system model, a source communicates with a destination in the presence of an untrusted relay and a powerful multi-antenna adversary jammer. The untrusted relay is an authorized necessary helper who may wiretap the confidential information. Meanwhile, the jammer is an external attacker who tries to damage both the training and transmission phases. Different from traditional frequency hopping spread spectrum (FHSS) techniques that require a pre-determined pattern between communicating nodes, in our scheme, the source and destination enjoy the local observations of the two-hop channels. Then they exploit the measured channel as the source of common randomness to generate shared secret keys. By collecting multiple time slots into a frame, the sequence of channels observed in each frame is utilized to specify the adopted FHSS sequence in the next frame. Based on the derived FHSS sequence from the key generation phase, the source starts to transmit its message supporting by the the destination-assisted cooperative jamming (DACJ) technique which prevents the untrusted relay from discovering the secret message. For the mentioned system model, we present new closed-form expressions for characterizing the achievable secret key rate (SKR) and ergodic secrecy rate (ESR) to highlight the efficiency of our proposed scheme compared to the state-of-the-art. We next determine the optimal power allocation (OPA) between the pilot and data transmission phases that maximizes the ESR performance while escaping from jamming attack. Finally, several numerical examples and discussions are presented to gain engineering insights behind the studied communication scenario.

Conflict Graph Based Concurrent Transmission Scheduling Algorithms for the Next Generation WLAN

Two conflict graph based concurrent transmission scheduling algorithms are proposed in this paper to efficiently solve the spatial TDMA (STDMA) scheduling problem for the next generation WLAN. Firstly, the STDMA scheduling problem for multiple timeslots is formulated as an multiple-step optimization problem. Secondly, a bi-weighted conflict graph is constructed to model the concurrent transmissions’ interference relationships, where the nodes denote the transmission request and the weights of the edges denote the interference level between any two transmission request nodes. If the interference between two transmission nodes is larger than the given interference threshold, then there are no edge between these two nodes. And only the acceptable interferences are modelled as the edges. Finally, a heuristic clique based algorithm (HCBA) and an optimal clique based algorithm (OCBA) are proposed, where HCBA assigns the transmission requests to the multiple timeslots one by one while OCBA assigns the transmission requests to the multiple timeslot once. The performance gap between the optimal one and the suboptimal one is evaluated. Simulation results show that HCBA not only has low complexity but also achieves similar performance comparing to OCBA.

SeqST-GAN

Citywide crowd flow data are ubiquitous nowadays, and forecasting the flow of crowds is of great importance to many real applications such as traffic management and mobility-on-demand (MOD) services. The challenges of accurately predicting urban crowd flows come from both the nonlinear spatial-temporal correlations of the crowd flow data and the complex impact of the external context factors, such as weather, holidays, and POIs. It is even more challenging for most existing one-step prediction models to make an accurate prediction across multiple future time slots. In this article, we propose a sequence-to-sequence (Seq2Seq) Generative Adversarial Nets model named SeqST-GAN to perform multi-step Spatial-Temporal crowd flow prediction of a city. Motivated by the success of GAN in video prediction, we for the first time propose an adversarial learning framework by regarding the citywide crowd flow data in successive time slots as “image frames.” Specifically, we first use a Seq2Seq model to generate a sequence of future “frame” predictions based on previous ones. Then, by integrating the generation error with the adversary loss, SeqST-GAN can avoid the blurry prediction issue and make more accurate predictions. To incorporate the external contexts, an external-context gate module called EC-Gate is also proposed to learn region-level representations of the context features. Experiments on two large crowd flow datasets in New York demonstrate that SeqST-GAN improves the prediction performance by a large margin compared with the existing state-of-the-art.

JOTE: Joint Offloading of Tasks and Energy in Fog-Enabled IoT Networks

Fog computing is a promising solution to enable delay-sensitive applications in the Internet of Things (IoT). In this article, based on the simultaneous wireless information and power transfer (SWIPT) technology, we investigate the joint offloading of tasks and energy (JOTE) in fog-enabled IoT networks. Specifically, the task node is allowed to offload energy and tasks to multiple neighboring helper nodes in a time-division multiple access (TDMA) manner. When there are no task queues in the nodes, the offloading decision for each task is independent. We first find the offloading strategy to minimize the task execution delay as well as the energy consumption for a specific task and then, analyze the condition under which the JOTE is beneficial. We show that it becomes more and more desirable to offload both the tasks and the energy from the task node as the number of helper nodes gets large. When there are task queues in the nodes, the offloading decision for each task becomes temporally correlated. We then characterize the optimal strategies to offload the tasks and energy jointly over multiple time slots. An online offloading policy based on the Lyapunov optimization is then proposed to minimize the time average expected delay while stabilizing the system operation. Comprehensive numerical results corroborate our theoretical results and demonstrate the superior performance of the proposed JOTE algorithms.

Mobility analysis of Modified Proportional Fair scheduler in LTE/LTE-Advanced system

Packet scheduling is one of the key schemes used in Radio Resource Management (RRM) for Long Term Evolution (LTE) cellular network. It serves as the resource allocation for each time and frequency dimensions in LTE baseband processing. In previous research, a new scheduling algorithm was developed, namely the Modified-Proportional Fair (PF) scheduler that splits a single subframe into multiple time slots and allocates the resource block (RB) to the identified User Equipment (UE) in some chosen time slots and it is done continuously for each subframe depending on the instantaneous Channel Quality Indicator (CQI) feedback received from UEs. Results have shown that the Modified-PF scheduler produces the most outstanding overall performance in terms of spectral efficiency and throughput with comparable fairness as compared to other state-of-the-art schedulers, namely, Round Robin and Proportional Fair schedulers. However, the performance of the new scheduler is not analysed in UE mobility scenario. Hence, this research will determine the type of response by the scheduler towards different mobility condition by simulating the throughput and the spectral efficiency of the three schedulers for various UE velocities. It is observed that the Modified-PF again shows significant performance improvement for various mobility condition in terms of average UE throughput and average UE spectral efficiency in both single cell omnidirectional and tri-sector eNodeB. This shows that Modified-PF can be considered as one of the packet scheduling options for the LTE cellular network.

Design Method of English Education Informationization Platform Based on 5G

In recent years, when carrying out educational activities, modern information technology and Internet technology have been integrated with each other to form a variety of educational information platforms, which have gradually replaced the traditional education and teaching methods. Using Internet thinking to improve the application level of education informatization is helpful to improve the quality of education and is of great significance to comprehensively promote the quality education of students. English is an important subject in student learning activities. English learning can improve the comprehensive ability of students, promote the healthy development of students, and enable students to better meet the needs of society. In order to improve learning efficiency, optimize the learning platform, and meet the needs of users, it is imperative to establish a 5G English education information platform. 80% of people in the current society are expecting the arrival of 5G platforms. Considering that in a high-density scenario, the number of terminals is large and the traffic is intensive. If the event scheduling method is still used to process data packets, there will be problems of too many event generations and too long processing time. Computing packet processing architecture. This architecture divides the time axis into multiple time slots. Based on the length and generation time of each data packet, the source terminal number of each data packet is mapped to the corresponding time slot position. By calculating the effective signals and interference in each time slot The strength of the signal is used to obtain performance indicators such as system capacity and throughput.

Compressive sensing based multiuser detector for massive MBM MIMO uplink

Media based modulation (MBM) is expected to be a prominent modulation scheme, which has access to the high data rate by using radio frequency (RF) mirrors and fewer transmit antennas. Associated with multiuser multiple input multiple output (MIMO), the MBM scheme achieves better performance than other conventional multiuser MIMO schemes. In this paper, the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed. This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots, which exploits the structured sparsity of these aggregate MBM signals. Under this kind of scenario, a multiuser detector with low complexity based on the compressive sensing (CS) theory to gain better detection performance is proposed. This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit (CoSaMP) and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals. By exploiting these sparsity, the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity. Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.

Base Station Switching and Sleep Mode Optimization With LSTM-Based User Prediction

The base station (BS) switching technique has recently attracted considerable attention for reducing power consumption in wireless networks. In this paper, we propose a novel BS switching and sleep mode optimization method to minimize the power consumption, while ensuring that the arriving user traffic is sufficiently covered. First, the user traffic in multiple time slots was predicted using the long-short term memory (LSTM) prediction model. Subsequently, we solved the Lyapunov optimization problem to obtain the optimal BS switching solution from the trade-off relationship between the reduced power consumption by BS switching and the user traffic handled in time series. Finally, we selected the sleep mode for the switched result by calculating the wake-up time and the power consumption ratio of each sleep mode. Simulation results confirm that the proposed algorithm successfully reduces the total power consumption by approximately 15% while preventing the user data queue from diverging in multiple time slots.

TDMA Scheduling in Spatially Extended LiFi Networks

Optical Wireless Communication (OWC) has attracted significant attention from academia and industry as a promising solution to complement traditional radio frequency communication. In Light-Fidelity (LiFi) networks, to enable soft handover and provide robustness against blockage of the line-of-sight links, LiFi receivers are designed to see multiple LiFi transmitters within their field-of-view. To trade-off spatial multiplexing with harmful interference, a proper user scheduling technique is required. In this work, we first derive practical and exact expressions for determining which simultaneous transmissions will create harmful interference and should be scheduled in multiple time-slots. Afterwards, relying on this expression, we propose our semi-distributed Spatially Extended TDMA algorithm, which is based on a time division contention–free access scheme. In contrast to more complex algorithms in the state-of-the-art, our scheduling protocol can reduce the computation time while also achieving a superior minimal user throughput. For a scenario with 9 transmitters and up to 15 receivers, our protocol is at least a factor 120 faster and can improve the minimal user throughput up to 91%, making it suitable for practical roll-out as a promising solution for very dense LiFi networks.

Self-Forming Multiple Sub-Nets Based Protocol for Tactical Networks Consisting of SDRs

The paper presents a novel approach for tactical networks in which radios form self-regulatory virtual sub-nets on the basis of control messages. The design uses hybrid of frequency division multiple access (FDMA) and time division multiple access (TDMA) approaches with less call setup delays and increases in network throughput. This multiple sub-nets based distributed algorithm exploits available spectrum resources, provides collision-free simultaneous transmissions and autonomous selection of time slots over different frequency sub-bands with self-organizing and self-forming network capabilities. We propose two schemes which provide multi-channel medium access control with autonomous scheduling of time slots for software-defined radios (SDRs). The schemes use request and acknowledgment frames as control messages to devise a distributed solution. These control messages alone help to form virtual sub-nets, preserve frequency channels and schedule transmissions over multiple time slot intervals, depend on the type of data messages. In order to demonstrate the behavior of sub-nets for tactical networks, theoretical findings are exploited with experimental analysis to provide practical implementation of schemes using contention-free time slotted common control channel for nodes coordination and time slotted collision-free multi-channel environment for data transmissions. The results show the effective coexistence of multiple transmissions in a network with increase in network throughput and lower the data latency up-to 76.8%, when compare to conventional MAC protocols. The design is workable for time sensitive, mission critical networks and expected to support multi-hop transmissions in similar manner.

Throughput Maximization of a Hybrid EH-SWIPT Relay System Under Temperature Constraints

This article considers the problem of throughput maximization for a hybrid energy harvesting and simultaneous wireless information and power transfer (EH-SWIPT) relay system subject to energy/temperature constraints at the transmitting/receiving nodes. An EH-based single antenna source sends information to a single-antenna destination via a cooperative half-duplex multi-antenna relay, wherein the relay applies power splitting (PS) technique for obtaining energy to forward information to the destination. It is also assumed that, the receiving nodes are subject to a peak temperature constraint. Two transmission scenarios are considered; Single time slot, and multiple ones. For both scenarios, achievable rate/throughput of the system is derived and optimal resource allocations, i.e. transmission powers of the source and the relay and the optimal PS ratios at the relay, are obtained. First the multiple time slots scenario is presented, and non-convexity of the optimization problem is tackled by proposing an iterative algorithm based on closed form expressions. Then, for the single time slot one, globally optimal resource allocations are obtained. For both scenarios, some special cases are considered to better reflect the performance characteristics of the system. Finally, numerical results are presented to highlight the effect of optimal resource allocation on system performance.

Legitimate Surveillance With Battery-Aided Wireless Powered Full-Duplex Monitor

This letter investigates legitimate surveillance of suspicious communication with a battery-aided full-duplex wireless powered monitor. The suspicious communication consists of multiple time slots, and the aim of the monitor is to maximize the number of slots that can be successfully wiretapped. To enhance the surveillance performance, the monitor can send jamming signals using the energy stored in the battery. It is assumed that the power splitting is used by the monitor for simultaneous energy harvesting and information decoding, and the harvested energy is accumulated in the battery for usage in future slots. The power splitting ratio and the jamming transmit power are optimized with the energy causality constraint under both the offline and online settings of the channel power gains. It is shown that all the proposed algorithms outperform the benchmark algorithm, and the proposed low-complexity suboptimal offline algorithm and the online algorithm are close to optimal.

Comment on ‘Performance analysis of energy harvesting communications using multipletime slots’

This note aims to report and correct a mistake in the mentioned paper by Min Long et al. An error occurs in the derivation of the average bit error rate for binary signals with non-coherent and coherent detection in Rayleigh fading channels. The corrected derivation is substantiated by the results of Numerical and Monte Carlo simulations.

Towards MYTHEN III - prototype characterisation of MYTHEN III.0.2

The MYTHEN detector is a single photon counting microstrip detector with 50 μm pitch developed at Paul Scherrer Institute for powder diffraction experiments at the Swiss Light Source. After more than ten years of operation of MYTHEN II, a new readout chip MYTHEN III was designed in 110 nm UMC technology to upgrade the current detector. It is designed to improve all aspects, specifically noise performance, count rate capability, threshold dispersion and frame rate. Each strip in the MYTHEN III chip features a dual polarity front end consisting of a charge sensitive amplifier and a shaper with variable gain and shaping time, as well as three comparators and three gateable 24-bit counters. The internal counting logic allows for different modes of operation: energy-windowing, charge sharing suppression, count rate improvement and pump-probe with multiple time slots. The architecture of the chip and its characterisation results will be presented. The first two prototypes have been tested in the lab and at the synchrotron. The RMS noise is reduced to 178 electrons (−24% compared to MYTHEN II) and thanks to the three thresholds in the chip, we can detect multiple analog signals in the shaper at high photon flux and thereby reach a count rate of 25 MHz per strip. Based on these results, a full scale chip with 128 channels was developed and sent to production.

Research on Optimal Access Location and Capacity of MultiStage Multi-Scenario Distributed Power Supply Based on OpenDSS

At present, the research on the planning problem of distributed power access distribution network is mostly carried out under the condition that the target annual load is known, and the impact of the differential load growth in different stages and the multi-scenario timing characteristics of the distribution network components are not considered. Aiming at this problem, an optimal access location and capacity calculation method for multi-period and multi-scenario distributed power supply based on OpenDSS is proposed. Firstly, the simulation principle and advantages of OpenDSS are explained from the aspects of model construction and power flow calculation. Secondly, the optimal power supply access model with multiple time slots and multiple scenarios is established with the goal of minimum planning end value. Thirdly, a model solving method based on particle swarm optimization is proposed. Finally, a typical example is chosen to calculate the optimal planning scheme of distributed power supply under multi-period, and the rationality of the model is verified.

A Switching-Based and Delay-Aware Scheduling Algorithm for Cognitive Radio Networks

In this article, an opportunistic inter-frame spectrum scheduler that maximizes the throughput of cognitive radio networks over a span of multiple time-slots is proposed. An optimization problem is formulated to find the optimum inter-frame scheduler while taking into account the switching delay, the primary user (PU) activity, historical information on the PU behavior, the channel quality as well as the secondary user (SU) status. Simulation results show that the proposed inter-frame scheduler significantly improved the overall aggregate throughput and average switching delay of the cognitive radio network when compared to the values obtained when scheduling is done on a slot-by-slot basis.

When to preempt? Age of information minimization under link capacity constraint

In this paper, we consider a scenario where a source continuously monitors an object and sends time-stamped status updates to a destination through a rate-limited link. We assume updates arrive randomly at the source according to a Bernoulli process. Due to the link capacity constraint, it takes multiple time slots for the source to complete the transmission of an update. Therefore, when a new update arrives at the source during the transmission of another update, the source needs to decide whether to skip the new arrival or to switch to it, in order to minimize the expected average age of information (AoI) at the destination. We start with the setting where all updates are of the same size, and prove that within a broadly defined class of online policies, the optimal policy should be a renewal policy, and has a sequential switching property. We then show that the optimal decision of the source in any time slot has threshold structures, and only depends on the age of the update being transmitted and the AoI at the destination. We then consider the setting where updates are of different sizes, and show that the optimal Markovian policy also has a multiple-threshold structure. For each of the settings, we explicitly identify the thresholds by formulating the problem as a Markov Decision Process (MDP), and solve it through value iteration. Special structural properties of the corresponding optimal policy are utilized to reduce the computational complexity of the value iteration algorithm.