Effective Capacity of URLLC over Parallel Fading Channels with Imperfect Channel State Information

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.

Effective capacity of cognitive radio systems in asymmetric fading channels

As known that the effective capacity theory offers a methodology for exploring the performance limits in delay constrained wireless networks, this article considered a spectrum sharing cognitive radio （CR） system in which CR users may access the spectrum allocated to primary users （PUs）. Particularly, the channel between the CR transmitter （CR-T） and the primary receiver and the channel between the CR-T and the CR receiver （CR-R） may undergo different fading types and arbitrary link power gains. This is referred to as asymmetric fading. The authors investigated the capacity gains achievable under a given delay quality-of-service （QoS） constraint in asymmetric fading channels. The closed-form expression for the effective capacity under an average received interference power constraint is obtained. The main results indicate that the effective capacity is sensitive to the fading types and link power gains. The fading parameters of the interference channel play a vital role in effective capacity for the looser delay constraints. However, the fading parameters of the CR channel play a decisive role in effective capacity for the more stringent delay constraints. Also, the impact of multiple PUs on the capacity gains under delay constraints has also been explored.

Optimization of Unbalanced Multi-stage Logistics Systems Based on Prüfer Number and Effective Capacity Coding

Unbalanced multi-stage logistics systems are optimized using an improved genetic algorithm based on the Prüfer number and the effective capacity coding. The improved decoding procedure uses the node capacity of the logistics system as an important factor, which influences the decoding procedure. As a result, any Prüfer number produced stochastically can be decoded to a feasible logistics pattern, which matchs the node capacities of the logistics system. With effective capacity coding, an unbalanced logistics system can be converted to a set of balanced systems. The effective capacity coding was combined with the Prefer number to construct the chromosome for the new method to search the whole solution space of the unbalanced multi-stage logistics system. Simulation results show that the new method finds a better solution with less computational time than st-GA. Although using a little more memory, the new method is still an efficient and robust method for optimizing unbalanced multi-stage logistics systems.

Ergodic Capacity Analysis and Adaptive Transsmion Scheme in Multi-user Distributed Antenna Systems

This paper focuses on analyzing the ergodic capacity performance of limited feedback (LFB) beamforming in multi-user distributed antenna system (DAS). In such a system, multi-user interference (MUI) is inevitably due to the channel uncertainties caused by quantization error. Considering this, we propose a parameter named effective ergodic capacity rate (EECR), which denotes the capacity offset between finite rate feedback and perfect channel state information (CSI). The simulation results show that the derived approximated EECR is very tight to actual EECR. Based on the approximated EECR, an adaptive minimum bit feedback scheme is proposed, which can effectively reduce the overhead of feedback channel and the complexity of the system. The simulation results verify the effectiveness of the proposed scheme.

Temperature Effects on Information Capacity and Energy Efficiency of Hodgkin-Huxley Neuron

Recent experimental and theoretical studies show that energy efficiency, which measures the amount of infor- mation processed by a neuron with per unit of energy consumption, plays an important role in the evolution of neural systems. Here we calculate the information rates and energy efficieneies of the Hodgkin-Huxley （HH） neuron model at different temperatures in a noisy environment. It is found that both the information rate and energy efficiency are maximized by certain temperatures. Though the information rate and energy efficiency cannot be maximized simultaneously, the neuron holds a high information processing capacity at the tempera- ture corresponding to the maximal energy efficiency. Our results support the idea that the energy efficiency is a selective pressure that influences the evolution of nervous systems.

Multi-QoS Guaranteed Resource Allocation for Multi-Services Based on Opportunity Costs

To meet the booming development of diversified services and new applications in the future, the fifth-generation mobile conmmnication system （5G） has arisen. Resources are increasingly scarce in the @namic time-varying of 5G networks. Allocating resources effectively and ensuring quality of service （QoS） requirements of multi-seiwices come to be a research focus. In this paper, we utilize effective capacity to build a utility function with multi-QoS metrics, including rate, delay bound and packet loss ratio. Taking advantage of opportunity cost （OC）, we also propose a multi-QoS guaranteed resource allocation algm＇ithm for multi-services to consider the future condition of system. In the algorithm, according to different business characteristics and the theory of OC, we propose different selection conditions for QoS users and best effort （BE） users to choose more reasonable resources. Finally, simulation results show that our proposed algorithm achieves superior system utility and relatively better fairness in multi-service scenarios.

Selection of proper combine harvesters to field conditions by an effective field capacity prediction model

Farmers have to finish their harvesting with high efficiency,because of time and cost.However,farmers are lacking knowledge and information required for selecting suitable combine harvesters and giving the conditions of their rice fields,because both information factors(combine harvester and field condition)impact the field capacity.The field capacity model was generated from combine harvesters with the Thai Hom Mali rice variety(KDML-105).Therefore,this study aimed to determine the prediction model for effective field capacity to combine harvesters when harvesting the Thai Hom Mali rice variety(KDML-105).The methods began by collecting data of 15 combine harvesters,such as field,crop,and machine conditions and operating times;to generate the prediction model for the KDML-105 variety.The prediction model was then validated using 12 combine harvesters that were collected similarly to the model creation.The results showed a root mean square error(RMSE)of 0.24 m^(2)/s for the model.The prediction model can be applied for farmers to select the proper combine harvesters and give their field conditions.

Effect of phosphodiesterase-5 inhibition on exercise capacity and clinical status in heart failure with preserved ejection fraction:A randomized clinical trial

Objective To determine the effect of the phosphodiesterase-5 inhibitor sildenafil compared with placebo on exercise capacity and clinical status in HFPEF. Design Multicenter, double-blind, placebo-controlled, parallel-group, randomized clinical trial of 216 sta- ble outpatients with HF, ejection fraction ≥ 50%, elevated N-terminal brain-type natriuretic peptide or elevat- ed invasively measured filling pressures, and reduced exercise capacity. Participants were randomized from October 2008 through February 2012 at 26 centers in North America. Follow-up was through August 30, 2012.

Resource allocation using time division multiple access over wireless relay networks

This article considers a wireless network consisting of multiple sources that communicate with the corresponding destination utilizing a single half-duplex relay, whereas, the sources use the relay opportunistically. By integrating the information theory with the concept of effective capacity, this article proposes a dynamic time allocation strategy over the wireless relay network that aims at maximizing the relay network throughput, subject to a given delay quality of service （QoS） constraint, where time division multiple access （TDMA） is applied in the relay network. The simulation results show that the proposed allocation strategy can significantly improve the effective capacity as compared to the traditional equal time allocation strategy.

Statistical QoS Guarantees for Energy Harvesting Cognitive Radio Networks

Spectrum and energy resources are very important for the rapidly developing of thefifth generation(5G)wireless communication networks.Cognitive radio and energy harvesting technologies,which focus on the spectrum efficiency and the energy efficiency,respectively,can be jointly used for solving the scarcities of spectrum and energy in energy harvesting cognitive radio networks(EHCRNs),where the energy is absorbed from ambient space and spectrum is licensed to the primary users.However,how to guarantee the quality of service(QoS)for EHCRNs is still a challenging problem.In this paper,we develop the optimal power and rate adaptation scheme under statistical QoS provisioning for EHCRNs.In particular,we analyze the power constraints of EHCRNs.Then,we formulate the effective capacity maximization problem for EHCRNs,solving which we obtain the closedform of the optimal power allocation and rate adaptation scheme under different power constraints.Numerical analyses verify the effective capacity enhancement and validate the relationships among the effective capacity,the QoS exponent,the energy arrival rate,and the average interference power.

Caching and D2D Assisted Wireless Emergency Communications Networks with Statistical QoS Provisioning

Along with natural disasters,the destruction of communication infrastructures leads to the congestion or failure of communication networks.Unmanned aerial vehicles(UAVs),which are with a high flexibility,can be employed as temporary base stations to establish emergency networks.To relieve the backhaul burden of UAVs,some imperative contents can be cached by terrestrial cache-enabled rescuers(CERs)and provide for victims with device-to-device(D2D)transmissions.To support the effectiveness and timeliness of emergency communication,the delay-bounded quality-of-service(QoS)requirement and network throughput are desired to be comprehensively considered,which imposes a new challenge for caching placement and CER deployment.In this paper,we focus on joint caching placement and CER deployment to maximize the effective capacity subject to delay-bounded QoS requirement.The overall non-convex problem is transformed into the caching placement and the CER deployment sub-problems.Then,we develop the QoS-aware caching placement scheme with fixed CER deployment density and obtain the QoS-aware CER deployment density with fixed caching placement.Based on the block-coordinate descent method,we also propose the joint caching placement and CER deployment scheme,which can not only effectively enhance average effective capacity but also guarantee the delay-bounded QoS requirement.Also,numerical simulations are conducted to show the performances of the proposed schemes.

Effects of tilt angle of disk plough on some soil physical properties, work rate and wheel slippage under light clay soil

Standard Disk Plough(SDP)is the integral element of traditional farming system in Middle and Northern Sudan.In SDP,the tilt angle between the planes of the cutting edge of the disk which is inclined to a vertical line may be altered according to the field conditions.Tractor drivers usually use an angle close to maximum in order to decrease the tillage depth,consequently decreasing power requirements,without considering the tillage quality and the impact on the soil properties.This experiment was conducted at the College of Agricultural Studies farm of Sudan University of Science and Technology to study the effects of three tilt angles(15°,20°and 25°)on soil bulk density,mean weight diameter,wheel slippage,work rate(or effective field capacity)and soil volume disturbed using mounted disk plough.The nature of soil on the farm found to be light clay.The theoretical forward speed was maintained at 6 km/h.The results showed that increasing tilt angle of the plough significantly(p<0.05)increased the bulk density,mean weight diameter and field capacity while significantly decreasing the tractor wheel slippage and soil volume disturbance.

Performance Analysis of the Reconfigurable Intelligent Surfaces Communication Systems

Reconfigurable intelligent surfaces (RIS) play a vital role in meeting the growing demand for higher data rates and reliability in wireless systems. This study focuses on analyzing the performance of RIS systems to gain a deeper understanding of their potential.The paper presents a mathematical analysis of the RIS system,deriving closed-form formulae that express its characteristics including signal-to-noise ratio(SNR)distribution,ergodic and effective capacity,outage,and error probability. The obtained formulae are newly derived and unconditionally valid solutions. Numerical results demonstrate a close agreement between the derived formulae and MonteCarlo simulation outcomes.