Channel Transmission Rate Research Articles

Investigation of 16 × 10 Gbps mode division multiplexed enabled integrated NGPON–FSO architecture under wired-wireless link losses

Abstract To enhance the transmission capacity for energy consumption and low cost system, mode division multiplexing (MDM) using mode 0 and mode 1 is proposed and investigated. A pair of eight downlink and uplink wavelengths is transmitted by using each MDM mode in an integrated bidirectional next generation passive optical network and free space optics (NGPON–FSO) system at 10 Gbps per channel transmission rate under the impact of FSO–fiber links impairments. Simulation results indicate that received power of −21.2 dBm with 0.2 dB power penalty can be obtained over 1 km FSO and 100 m multimode fiber under unfavourable turbulent effects. The system provides extended FSO link range, and fiber range of 150 km and 600 m respectively at threshold limit of 10−3. Besides, the mathematical analysis depicts the receiver sensitivity and splitter power budget of 42 dBm and 18 dB, respectively, for the proposed system. The system offers finest performance than other pre-existing systems.

A flexible algorithm to offload DAG applications for edge computing

Multi-access Edge Computing (MEC) is an enabling technology to leverage new network applications, such as virtual/augmented reality, by providing faster task processing at the network edge. This is done by deploying servers closer to the end users to run the network applications. These applications are often intensive in terms of task processing, memory usage, and communication; thus mobile devices may take a long time or even not be able to run them efficiently. By transferring (offloading) the execution of these applications to the servers at the network edge, it is possible to achieve a lower completion time (makespan) and meet application requirements. However, offloading multiple entire applications to the edge server can overwhelm its hardware and communication channel, as well as underutilize the mobile devices’ hardware. In this paper, network applications are modeled as Directed Acyclic Graphs (DAGs) and partitioned into tasks, and only part of these tasks are offloaded to the edge server. This is the DAG application partitioning and offloading problem, which is known to be NP-hard. To approximate its solution, this paper proposes the FlexDO algorithm. FlexDO combines a greedy phase with a permutation phase to find a set of offloading decisions, and then chooses the one that achieves the shortest makespan. FlexDO is compared with a proposal from the literature and two baseline solutions, considering realistic DAG applications extracted from the Alibaba Cluster Trace Program. FlexDO results are consistently only 3.9% to 8.9% above the optimal makespan in all test scenarios, which include different levels of CPU availability, a multi-user case, and different communication channel transmission rates. FlexDO outperforms both baseline solutions by a wide margin, and is three times closer to the optimal makespan than its competitor. It achieves up to 87% similarity with the optimal decision and does not burden the edge server.

Performance Modeling of an NR-U and WiFi Coexistence System Using the NR-U Category-4 LBT Procedure and WiFi DCF Mechanism in the Presence of Hidden Nodes

The hidden-node problem is an important problem that should be considered in the design of a wireless communication system. This paper studies the performance modeling of an NR-U and WiFi coexistence system using the NR-U category-4 LBT procedure and WiFi DCF mechanism in the presence of hidden nodes. 2-D Markov models are first developed to describe the NR-U category-4 LBT procedure of an NR-U gNB and the WiFi DCF procedure of a WiFi AP, respectively, taking into account the effects of hidden nodes. Based on the two Markov models, theoretical models are further derived for analyzing the throughput of a gNB/AP and the delay of an NR-U/WiFi packet. Finally, the derived theoretical models are validated through simulation results and based on the theoretical models, the impacts of major system parameters on the system performance in terms of the throughput and packet delay are investigated, including the data packet arrival rate, the density, the sensing distance, and the channel transmission rate of a gNB.

Performance Modeling of an NR-U and WiFi Coexistence System Using the NR-U Category-4 LBT Procedure and 802.11e EDCA Mechanism in the Presence of Hidden Nodes

This paper studies the performance modeling of an NR-U and WiFi coexistence system using the NR-U category-4 LBT procedure and 802.11e EDCA mechanism in the presence of hidden nodes. 3-D Markov models are first developed to describe the NR-U category-4 LBT procedure for a priority-p queue of an NR-U gNB and the 802.11e EDCA mechanism for an AC-q queue of a WiFi AP, taking into account the effects of hidden nodes and the transmission of different-priority data. Based on the Markov models, theoretical models are derived for analyzing the mean throughput of a priority-p queue in an NR-U gNB and that of an AC-q queue in a WiFi AP as well as the mean transmission delay of an NR-U priority-p data packet and that of a WiFi AC-q data packet. The derived theoretical performance models are validated through simulation results. Based on the performance models, the impacts of major system parameters on the system performance are investigated, including the density of NR-U gNBs, the sensing distance and channel transmission rate of an NR-U gNB, and the data packet arrival rate at an NR-U gNB.

Energy-efficient CH selection protocol for mobile smart dust network

Despite the fact that smart dust networks (SDNs) were in usage for more than ten years, numerous contemporary activities, including emergency management, environmental sensing, and healthcare observation, largely rely on them today. In besides having a small channel transmission rate, this form of system has a limited power capacity and a restricted existence. Because of the significant impact that communication costs have on the energy consumption of smart dust nodes, connectivity is one of these systems' greatest problems. Among the most effective methods for conserving SDN energy has indeed been demonstrated to be clustering. Among the most essential sensor network clustering protocols is LEACH (low energy adaptive clustering hierarchy). Furthermore, there are significant issues with this protocol, particularly when Cluster head (CH) is chosen randomly during setup. The purpose of this research is to improve smart dust environment by selecting a CH based on its energy consumption level. The outcomes show how effective this work is at enhancing IE2-LEACH and EESR while extending the lifespan and enhancing SDN effectiveness.

Study of Channel Capacity Optimization of Discrete Channel Based on Normalized Tangent Function

Channel capacity is the rate limit of information transmission; many researchers strive to find the maximum channel transmission rate while balancing the performance of the whole communication system and making it close to the channel capacity. We know in the discrete channel that, when the BER of the system is small enough, the transmission rate of the channel will be extremely close to the channel capacity. According to Shannon theory, the common way to increase the channel capacity is to increase the system bandwidth and the input signal power. However, the bandwidth resources are extremely limited, so it is impractical to expand the system bandwidth, and at the same time, increasing the input signal power is impractical as well, because it will reduce the economy of the communication system. In this paper, we proposed a normalized tangent function (NorTF) which can optimize the discrete channel probability distribution, reduce the BER of the channel, and improve the channel capacity of the discrete channel, which need not expand bandwidth and increase the signal input power of the system. Through theoretical analysis and experimental verification of this method, we found that the channel capacity of the improved system was indeed much higher than that of the preimproved system, so the method proposed in this paper has some theoretical guiding significance and is feasible.

Deep Reinforcement Learning-Based Spectrum Allocation Algorithm in Internet of Vehicles Discriminating Services

With the rapid development of global automotive industry intelligence and networking, the Internet of Vehicles (IoV) service, as a key communication technology, has been faced with an increasing spectrum of resources shortage. In this paper, we consider a spectrum utilization problem, in which a number of co-existing cellular users (CUs) and prioritized device-to-device (D2D) users are equipped in a single antenna vehicle-mounted communication network. To ensure a business-aware spectrum access mechanism with delay granted in a complex dynamic environment, we consider optimizing a metric that maintains a trade off between maximizing the total capacity of vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) links and minimizing the interference of high priority links. A low complexity priority-based spectrum allocation scheme based on the deep reinforcement learning method is developed to solve the proposed formulation. We trained our algorithm using the deep Q-learning network (DQN) over a set of public bandwidths. Simulation results show that the proposed scheme can allocate spectrum resources quickly and effectively in a high dynamic vehicle network environment. Concerning improved channel transmission rate, the V2V link rate in this scheme is 2.54 times that of the traditional random spectrum allocation scheme, and the V2I link rate is 13.5% higher than that of the traditional random spectrum allocation scheme. The average total interference received by priority links decreased by 14.2 dB compared to common links, realized service priority distinction and has good robustness to communication noise.

Self-triggering adaptive optimal control for nonlinear systems based on encoding mechanism

This paper deals with self-triggering adaptive optimal control for nonlinear continuous-time systems. We propose a novel self-triggering control structure concerning a special encoding mechanism, which combines the trigger time of control and sampling and reduces both the control time and the sampling time. Such a triggering structure ensures the existence of a maximum triggering time in self-triggering control. When the system expression is known, the encoding mechanism will lead to high quantitative accuracy at a limited channel transmission rate. Moreover, we also provide a new control algorithm and triggering conditions of the proposed structure. Specifically, this algorithm solves the optimal control strategy by using the cost function approximated by neural networks. Besides, the derived closed-loop system is proven to be asymptotically stable. Finally, two examples are provided to illustrate the effectiveness of the proposed control method.

ANALYSIS OF TELECOMMUNICATION CHANNEL SPECTRAL CHARACTERISTICS WITH BLOCK CODING AT A CONSTANT SPEED OF THE MESSAGE SOURCE

Background. The direction of development of modern electronic communication systems tends to increase the speed of information transmission. In turn, increasing the speed requires the use of additional resources of the communication channel and tools to maintain the specified reliability of the transmission under limited conditions. But resources are not free. That is why there is a need to establish a relationship between the conditions for reliable transmission in high-speed channels and the spectral and energy parameters of the information transmission system.
 Objective. The purpose of the paper is to analyse and describe the effect of block noise-tolerant coding on the rate of transmission of symbols in the communication channel while ensuring the required reliability of information transmission at a constant speed of the message source by increasing the frequency involved.
 Methods. The initial stage of the study is the presentation of system parameters in case of inaccurate transmission. Then a block redundant code is synthesized, which ensures the reliability of information transmission and the procedure of spreading the spectrum at a fixed speed of the message source is performed.
 Results. Recommendations on the method of selecting coding parameters in the procedure of spreading the spectrum and provided that the speed of the message source is constant are formed.
 Conclusions. Analysis of the possibilities of noise-tolerant coding at different energies of the communication channel under conditions of increasing the channel transmission rate at a fixed speed of the message source.
 Keywords: speed; message source; reliability; noise immunity.

Towards Enabling Multihop Wireless Local Area Networks for Disaster Communications

xCalamities such as earthquakes and tsunami affect communication services by devastating the communication network and electrical infrastructure. Multihop relay networks can be deployed to restore the communication environment quickly in catastrophe‐stricken areas. However, performance in terms of throughput is affected by deploying the relay networks. In wireless local area networks (WLANs), the primary purpose of multiband transmission employing multihop relay networks is to increase the throughput and reduce the latency. In the future, wireless networks are believed to carry high throughput, more data rates, and less latency by expanding bandwidth‐demanding applications. Simultaneous multiband transmission in WLAN systems is considered to increase the coverage area without power escalation. Due to the inherent characteristics of different bands and channel conditions, transmission rates tend to be different. The impact of such conditions may cater to the disproportional distribution of data among bands, causing some of the bands to be overwhelmed, which incurs buffer overflow and packet loss. In contrast, the channel capacity of some of the bands remains underutilized. In this paper, we consider the channel conditions and transmission rates of each band on either side of the relay to address the problems mentioned above. Furthermore, this paper proposes a load distribution‐based end‐to‐end traffic scheduling technique to improve system performance. The simulation results demonstrate the effectiveness of our proposed method with maximizing throughput and minimizing end‐to‐end delay.

Physical principles of operation and basic capabilities of the four channel receiver 1288хк1т (mf-01)

In radar detection and radio navigation ensuring the reception of signals transmitted over the meteor channel of radio communication is often controversial[1-3]. Solving these problems requires the ability to synthesize precision signals directly[4, 5] for heterodyning systems in addition to modern analog-to-digital conversion devices, correlation analysis, and statistical processing of signal-noise complex. The step of adapting four channel receivers to dynamically changing conditions of transmitting information may include determining the composition of the signal-noise mixture, determining the phase characteristics of the communication channel, estimating the channel transmission rate, and obtaining QoS information. In addition, adaptation often implies the use of a logical channel control loop, which entails the need for complex feedback procedures. Software-defined radio systems are radio and telecommunication systems that can be tuned to an arbitrary frequency band and receive various types of modulated signal, consisting of programmable equipment with program control. SDR performs a significant part of digital signal processing on a conventional personal computer, signal processor or FPGA. In such systems and complexes, the parameters are changed by software configuration. The article considers the implementation of DDS for heterodyning an intermediate frequency signal on the FPGA basis for four channel receiver 1288хк1т (mf-01), which allows you to work with both narrow-band and wide-band communication channels (with simultaneous operation of 4 channels, the band can be expanded) and can be used in modern telecommunication communication systems.

Complex-Valued Neural Network Design for Mitigation of Signal Distortions in Optical Links

Nonlinearity compensation is considered as a key enabler to increase channel transmission rates in the installed optical communication systems. Recently, data-driven approaches - motivated by modern machine learning techniques - have been proposed for optical communications in place of traditional model-based counterparts. In particular, the application of neural networks (NN) allows improving the performance of complex modern fiber-optic systems without relying on any a priori knowledge of their specific parameters. In this work, we introduce a novel design of complex-valued NN for optical systems and examine its performance in standard single mode fiber (SSMF) and large effective-area fiber (LEAF) links operating in relatively high nonlinear regime. First, we present a methodology to design a new type of NN based on the assumption that the channel model is more accurate in the nonlinear regime. Second, we implement a Bayesian optimizer to jointly adapt the size of the NN and its number of input taps depending on the different fiber properties and total length. Finally, the proposed NN is numerically and experimentally validated showing an improvement of 1.7 dB in the linear regime, 2.04 dB at the optimal optical power and 2.61 at the max available power on Q-factor when transmitting a WDM 30 × 200G DP-16QAM signal over a 612 km SSMF legacy link. The results highlight that the NN is able to mitigate not only part of the nonlinear impairments caused by optical fiber propagation but also imperfections resulting from using low-cost legacy transceiver components, such as digital-to-analog converter (DAC) and Mach-Zehnder modulator.

Low bit rate underwater video image compression and coding method based on wavelet decomposition

In view of the limited bandwidth of underwater video image transmission, a low bit rate underwater video compression coding method is proposed. Based on the preprocessing process of wavelet transform and coefficient down-sampling, the visual redundancy of underwater image is removed and the computational coefficients and coding bits are reduced. At the same time, combined with multi-level wavelet decomposition, inter frame motion compensation, entropy coding and other methods, according to the characteristics of different types of frame image data, reduce the number of calculations and improve the coding efficiency. The experimental results show that the reconstructed image quality can meet the visual requirements, and the average compression ratio of underwater video can meet the requirements of underwater acoustic channel transmission rate.

Routing With Intelligent Spectrum Assignment in Full-Duplex Cognitive Networks Under Varying Channel Conditions

Recent developments of self-interference suppression techniques have enabled practical implementations of full-duplex (FD) cognitive-radio (CR) communication systems. Such systems can significantly enhance spectrum utilization by allowing a CR user to simultaneously transmit and receive over the same frequency channel. However, the CR FD-capabilities challenge the effectiveness of existing CR-based routing protocols as joint FD-aware channel-assignment and routing are essential to enhance network performance. In this letter, we propose a joint FD-aware channel-assignment and route selection protocol in FD-based CR networks (CRNs) under time-varying channel conditions and transmission rates. Specifically, for a given set of paths between a CR source-destination pair, our protocol computes the channel-assignment over each path that maximizes the end-to-end network throughput subject to interference constraints. This assignment problem is shown to be an NP-hard binary linear programming (BLP) that can be sub-optimally solved in polynomial-time using the sequential-fixing procedure. Then, our protocol determines the path with the highest end-to-end network throughput. Simulation results reveal that our proposed routing protocol significantly improves the end-to-end throughput compared to previous FD-aware routing protocols.

Control Code Multiple Encryption Algorithm on Satellite-to-ground Communication

The transmission security between ground station and satellite is challenging. Some existing multistep algorithms leave lots of loopholes for eavesdropping and attacking in satellite-to-ground communication. For high security, optical communication is a promising solution. In this paper, we propose a control code multiple encryption algorithm (CCMEA) for the single-photon-transmission between satellite and ground station. CCMEA can utilize the control code to respectively encrypt three cognitive optimization sections: loop iteration, polarization coding and order rearrangement, and simulation shows that CCMEA can realize one step transmission to decrease loopholes compared with multistep encryption algorithm. In addition, we design a security detection method by combining the decoy photon analysis and the quantum bit error rate (QBER) analysis. The numerical results show that CCMEA can reduce the security threshold by 27% compared with multistep encryption algorithm of BB84 scheme. Finally, for satellite-to-ground communication, we construct an analytic QBER model on CCMEA with four factors: quantum channel transmission rate, single-photon acquisition probability, measurement factor and data filtering factor. The result demonstrates the effectiveness of CCMEA on satellite-to-ground communication.

Channel Estimation and Data Transmission in Massive MIMO TDD Systems

This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.

A real-time power monitoring and energy-efficient network/interface selection tool for android smartphones

Energy efficiency in wireless and cellular networks has become one of the most important concerns for both academia and industry due to battery dependence of mobile devices. In this regard, Wireless Network Interface Cards (WNICs) of mobile devices have to be taken into account carefully as they consume an important chunk of the system's total energy. In this paper, we propose a real-time network power consumption profiler and an energy-aware network/interface selection tool for Android-based smartphones. The tool has been freely released on the Android Play Store. The proposed solution reports the power consumption levels of different network interfaces (Wi-Fi and Cellular) by making use of actual packet measurements and precise computations, and enables the devices to handover horizontally/vertically in order to improve the energy efficiency. In this context, widespread analyses have been executed to show the accuracy of the proposed tool. The results demonstrate that the proposed tool is very accurate for any type of IEEE 802.11 wireless or cellular stations, regardless of having different amount of channel utilization, transmission rates, signal strengths or traffic types.

Modeling and measurement of microwave propagation multipath channels in drill pipe bore

AbstractIn this paper, the characteristics of microwave propagation channels in drill pipe bore are analyzed by regarding the drill pipe as an irregular lossy cylindrical waveguide. An attenuation law is modeled using multipath propagation theory and an experimental statistical method. It is shown from physical measurement results that 5″ and $5^{1/2 \prime \prime} $ drill pipe bores, widely applied in the field of air drilling, can be used as 2.4 GHz band microwave channels with the caveat that the numerous reflective surfaces in the joint section of the drill pipe produce a great deal of reflected waves. Hence, the drill pipe bore has the characteristics of a dual cluster multipath channel, and multipath fading and delay are the primary factors affecting propagation quality. The study's constructed microwave attenuation model, based on multipath channels, can be regarded as the average attenuation of the unit length in the drill pipe bore, and can be used as the basis for simulation and analysis of the longer drill pipe string. In addition, a large delay between the two clusters leads to a significant increase of the root mean square delay spread. Consequently, multipath fading and delay are the main factors affecting the channel transmission rate.

Information trimming: Sufficient statistics, mutual information, and predictability from effective channel states.

One of the most basic characterizations of the relationship between two random variables, X and Y, is the value of their mutual information. Unfortunately, calculating it analytically and estimating it empirically are often stymied by the extremely large dimension of the variables. One might hope to replace such a high-dimensional variable by a smaller one that preserves its relationship with the other. It is well known that either X (or Y) can be replaced by its minimal sufficient statistic about Y (or X) while preserving the mutual information. While intuitively reasonable, it is not obvious or straightforward that both variables can be replaced simultaneously. We demonstrate that this is in fact possible: the information X's minimal sufficient statistic preserves about Y is exactly the information that Y's minimal sufficient statistic preserves about X. We call this procedure information trimming. As an important corollary, we consider the case where one variable is a stochastic process' past and the other its future. In this case, the mutual information is the channel transmission rate between the channel's effective states. That is, the past-future mutual information (the excess entropy) is the amount of information about the future that can be predicted using the past. Translating our result about minimal sufficient statistics, this is equivalent to the mutual information between the forward- and reverse-time causal states of computational mechanics. We close by discussing multivariate extensions to this use of minimal sufficient statistics.

Layered Constructions for Low-Delay Streaming Codes

We propose a new class of error correction codes for low-delay streaming communication. We consider an online setup where a source packet arrives at the encoder every $M$ channel uses, and needs to be decoded with a maximum delay of $T$ packets. We consider a sliding-window erasure channel --- $\cC(N,B,W)$ --- which introduces either up to $N$ erasures in arbitrary positions, or $B$ erasures in a single burst, in any window of length $W$. When $M=1$, the case where source-arrival and channel-transmission rates are equal, we propose a class of codes --- MiDAS codes --- that achieve a near optimal rate. Our construction is based on a {\em layered} approach. We first construct an optimal code for the $\cC(N=1,B,W)$ channel, and then concatenate an additional layer of parity-check symbols to deal with $N>1$. When $M > 1$, the case where source-arrival and channel-transmission rates are unequal, we characterize the capacity when $N=1$ and $W \ge M(T+1),$ and for $N>1$, we propose a construction based on a layered approach. Numerical simulations over Gilbert-Elliott and Fritchman channel models indicate significant gains in the residual loss probability over baseline schemes. We also discuss the connection between the error correction properties of the MiDAS codes and their underlying column distance and column span.