Age of information analysis for internet of things information status update system with cellular backhaul and dedicated energy harvesting beacons

The Internet of Things (IoT) that is usually deployed with the assistance of cellular backhaul and energy harvesting (EH) is characterized by the status update freshness. However, the traditional nature EH results in the loss of information freshness due to the randomness of nature energy process. Although using wireless energy transferring (WET) to charge sensors can overcome this problem, this method has low-energy efficiency. With these considerations, this paper proposes a novel IoT system under cellular communication scenario by simultaneously exploiting the nature EH and WET. The proposed IoT system is consisted of a cellular backhaul subsystem, a wireless EH and transferring (WEHT) subsystem, and a wireless sensor status update subsystem. The WEHT subsystem employs the dedicated power beacons harvesting energy from natural energy source and transferring the harvested energy to sensor. For the proposed IoT system, this paper first investigates the WEHT subsystem and constructs the Markov Chain (MC) of discrete energy states as well as the MC state transition matrix. Second, the average AoI and peak AoI (PAoI) are formulated by separately considering cellular backhaul and EHTBs. The AoI (PAoI) comparison shows that the proposed EHTB-based IoT system can outperform the conventional non-EHTB one where the sensor directly harvests energy from natural source. At the same time, the numerical results exploit the impact of system parameters on AoI and PAoI, respectively. It is found that there exists a trade-off between the nature energy arrival and EHTB energy transfer so that the average minimum AoI and PAoI are achieved.     

短包传输下缓冲区辅助的无线传感器状态更新系统的信息新鲜度研究

考虑到信息新鲜度对无线传感器状态更新系统设计和部署带来的影响,提出一个由两个传感器源节点和一个公共目的节点组成的状态更新系统。该系统中两个传感器源节点均配备一个单位大小的缓冲区,并根据伯努利过程在每个时隙感知对应物理过程的状态更新。随后传感器以有限块长度短包的形式将状态更新发送至目的节点。该文采用信息年龄（Age of Information,AoI）描述状态更新的新鲜度。首先,以传感器缓冲区状态组合为中心,该系统可建模为连续时间有限状态的马尔可夫过程,其中有限状态表示缓冲区的不同状态,连续时间表示与年龄相关过程的演进。因此,该系统平均AoI可采用随机混合系统（Stochastic Hybrid System,SHS）评估。最后仿真结果表明,当更新包的感知概率为0.2时,信噪比从0 dB增加至3 dB将导致平均AoI降低20.6%;当信噪比固定为4 dB时,状态更新包块长度从300 channel uses增长至400 channel uses会致使平均AoI降低8.8%。该研究可为缓冲区辅助的状态更新系统设计提供基本理论依据。     

能量收集认知无线电网络下的多接入用户信息年龄研究

针对信道资源有限的多接入信道无线传感器网络场景,实时信息的传送需要考虑信道环境和信息新鲜度问题。该文基于认知无线电物联网（Cognitive Radio-Internet of Things, CR-IoT）系统,构建了一个具有频谱访问权限的主用户（Primary User, PU）和两个可共享PU频谱次用户（Secondary User, SU）的网络模型。在考虑PU工作状态和SU数据队列稳定的条件下,提出了一个以最小化节点平均AoI为目标的优化问题。其次使用两种策略进行优化,包括概率随机接入策略（Probabilistic Random Access Policy, PRA）,该策略下两个SU节点根据相应的概率分布做出独立的传输决策;以及基于李雅普诺夫优化框架优化时隙内调度决策的漂移加罚策略（Drift Plus Penalty Policy, DPP）。仿真结果可知,DPP策略下得到的平均AoI的值要明显低于PRA策略,表明使用DPP策略对平均AoI的优化更加显著,可以有效提升数据包的时效性和新鲜度。      

基于无人机辅助的认知无线电网络信息年龄研究

考虑到信息时效性和数据新鲜度对各类实时状态更新系统带来的挑战,提出了一种无人机（Unmanned Aerial Vehicle, UAV）中继辅助的认知无线电网络（Cognitive Radio Network, CRN）信息年龄（Age of Information, AoI）最小化方案。为了降低CRN中次用户接收机处的AoI,在不影响主用户正常通信的前提下,利用UAV作为移动中继来辅助次用户发射机将数据包传输到对应的接收机。通过联合优化UAV的飞行轨迹和资源分配来确保信息新鲜度。由于联合设计问题是非凸的,故采用连续凸逼近的高效迭代算法得出问题的最优解。仿真结果表明,所提方案可以有效提高信息新鲜度,并获得峰值AoI的最小值。同时,数据包的大小和数量与AoI呈线性关系,对UAV的飞行轨迹也有影响。      

基于信息年龄优化的多信道无线网络调度方法

信息年龄(AoI)是近年来针对时间敏感类应用所提出的一种描述数据交付及时性的度量标准,它是从网络中目标节点的角度出发,衡量其最新收到的数据包的新鲜程度.在信道资源受限的多信道无线网络场景中,基于信息年龄的链路调度问题需要考虑信道资源和链路冲突的约束.针对上述问题,该文提出一种逐时隙调度链路进行数据传输的调度方法,以最小...     

基于部分中继选择的能量收集双跳网络信息年龄优化

针对传统中继协作网络传感器节点能量受限导致信息传输延迟较高的问题,将短包通信（SPC）和能量收集技术相结合,构建了一种双跳中继无线传感器网络模型。网络中源节点和中继均需从专用能量基站收集射频信号能量以保证信息的持续传输,中继采用半双工解码转发协议将源节点发送的状态更新信息以短包形式传递到目的节点,利用中继选择策略与最大比合并技术提出了基于时效性的最早部分中继选择方案。考虑该网络信息的新鲜度,首先,分析了SPC传输性能,推导了中继和目的节点处的平均包错误率。其次,利用顺序统计量描述了源节点到中继端数据包的重传次数,基于更新过程理论推导了网络的平均信息年龄（AoI）表达式,并采用梯度下降方法优化了影响网络平均AoI的部分参数。最后,仿真分析结果表明,优化中继数量和数据包长度可以有效提高网络信息新鲜度,同时,通过对比优化部分参数得到的最优值与贪婪方法得到的最小化平均AoI理论值,可以验证部分中继协作方案在双跳状态更新网络中的可行性。      

雾无线接入网中基于内容流行度和信息新鲜度的缓存更新策略

将边缘缓存技术引入雾无线接入网,可以有效减少内容传输的冗余。然而,现有缓存策略很少考虑已缓存内容的动态特性。该文提出一种基于内容流行度和信息新鲜度的缓存更新算法,该算法充分考虑用户的移动性以及内容流行度的时空动态性,并引入信息年龄(AoI)实现内容的动态更新。首先,所提出算法根据用户的历史位置信息,使用双向长短期记忆网络(Bi-LSTM)预测下一时间段用户位置;其次,根据预测得到的用户位置,结合用户的偏好模型得到各位置区的内容流行度,进而在雾接入点进行内容缓存。然后,针对已缓存内容的信息年龄要求,结合内容流行度分布,通过动态设置缓存更新窗口以实现高时效、低时延的内容缓存。仿真结果表明,所提算法可以有效地提高内容缓存命中率,在保障信息的时效性的同时最大限度地减小缓存内容的平均服务时延。     

Channel quality estimation and rate adaptation for cellular mobileradio

We propose a technique to measure channel quality in terms of signal-to-interference plus noise ratio (SINR) for the transmission of signals over fading channels. The Euclidean distance (ED) metric, associated with the decoded information sequence or a suitable modification thereof, is used as a channel quality measure. Simulations show that the filtered or averaged metric is a reliable channel quality measure which remains consistent across different coded modulation schemes and at different mobile speeds. The average scaled ED metric can be mapped to the SINR per symbol. We propose the use of this SINR estimate for data rate adaptation, in addition to mobile assisted handoff (MAHO) and power control. We particularly focus on data rate adaptation and propose a set of coded modulation schemes which utilize the SINR estimate to adapt between modulations, thus improving the data throughput. Simulation results show that the proposed metric works well across the entire range of Dopplers to provide near-optimal rate adaptation to average SINR. This method of adaptation averages out short-term variations due to Rayleigh fading and adapts to the long-term effects such as shadowing. At low Dopplers, the metric can track Rayleigh fading and match the rate to a short-term average of the SINR, thus further increasing throughput     

Scheduling with base station diversity and fairness analysis for the downlink of CDMA cellular networks

Efficient packet scheduling in CDMA cellular networks is a challenging problem due to the time variant and stochastic nature of the channel fading process. Selection diversity is one of the most effective techniques utilizing random and independent variations of diverse channels to improve the performance of communication over fading channels. In this paper, we propose two packet scheduling schemes exploiting base station selection diversity in the downlink of CDMA cellular networks. The proposed schemes rely on the limited instantaneous channel state information (CSI) to select the best user from the best serving base station at each time slot. This technique increases the system throughput by increasing multiuser diversity gain and reducing the effective interference among adjacent base stations. Results of Monte Carlo simulations are given to demonstrate the improvement of system throughput using the proposed scheduling schemes. In addition, we investigate fairness issue of wireless scheduling schemes. Due to different characteristics of wireless scheduling schemes, the existing fairness indexes may result in misleading comparison among different schemes. We propose a new fairness index to compare the overall satisfaction of the network users for different scheduling schemes. Copyright © 2006 John Wiley & Sons, Ltd.     

基于强化学习的非正交多址接入和移动边缘计算联合系统信息年龄更新

物联网发展对信息时效性的需求越来越高,信息新鲜度变得至关重要。为了维持信息新鲜度,在非正交多址接入(NOMA)和移动边缘计算(MEC)的联合系统中,对多设备单边缘计算服务器的传输场景进行了研究。在该场景中,如何分配卸载任务量和卸载功率以最小化平均更新代价是一个具有挑战性的问题。该文考虑到现实中的信道状态变化情况,基于多代理深度确定性策略梯度(MADDPG)算法,考虑信息新鲜度影响,建立了最小化平均更新代价的优化问题,提出一种寻找最优的卸载因子和卸载功率决策。仿真结果表明,采用部分卸载的方式可以有效地降低平均更新代价,利用MADDPG算法可以进一步优化卸载功率,经比较,MADDPG算法在降低平均更新代价方面优于其他方案,并且适当地减少设备数量在降低平均更新代价方面效果更好。     

一种改进的IR-HARQ功率分配方案

为了保证信息在无线衰落信道条件下的稳定传输,提出了一种基于正交幅度调制(Quadrature Amplitude Modulation,QAM)的增量冗余混合自动重传请求(Incremental Redundancy Hybrid Automatic Repeat Request,IR-HARQ)功率分配方案,计算了基于QAM的IR-HARQ传输链路的互信息,以提高数据吞吐率为目的提出了混合传输策略.在瑞利衰落信道下将该方案与最大化互信息策略和逆信道策略进行Matlab仿真比较,结果显示提出的混合传输策略有更高的数据吞吐率,且随着重传次数的增加,数据吞吐率迅速接近遍历容量.     

基于信息年龄的工业无线传感器网络混合数据调度方法

在工业无线传感器网络(IWSN)中，实时交付工业现场的周期性控制/传感数据流与非周期性事件数据流，是保障生产安全高效运行的关键。信息年龄(AoI)作为一种新兴的数据新鲜度衡量指标，能够从目标节点角度全面地度量网络数据交付的实时性。针对周期性和非周期性数据混合的工业无线传感器网络，该文在引入网络数据整体新鲜度指标的同时，考虑到周期性数据新鲜度在超过阈值后可能会对工业生产造成负面影响，建立了最小化系统平均AoI和周期性数据AoI逾期概率的联合优化模型，并将优化问题表述为马尔可夫决策过程(MDP)进行求解。由于传统基于相对值迭代的最优求解方法在大规模网络中因为维度灾难难以实施，因此采用深度强化学习(DRL)降低优化问题的状态空间维度，并改进决策探索机制以加快学习速度，提出了基于优化决策探索的深度强化学习(DRL-ODE)调度方法。仿真结果表明，所提方法能够提高网络数据交付的实时性，并有效减少周期性数据的AoI逾期概率。     

Bandwidth efficient transceiver design for differentially encoded OFDM system

In this paper, we present a bandwidth efficient non-coherent transceiver design for single input single output orthogonal frequency division multiplexing (SISO-OFDM) modulation with differential encoding. Under fast channel fading or in low signal-to-noise ratio (SNR) regime, pilot assisted channel estimation is not feasible. In such channel conditions, conventional non-coherent detection methods are not reliable resulting in poor throughput. We propose a frequency-spread time-encoded (FSTE) method for OFDM modulation, which exploits multipath diversity and achieves target energy-per-bit to noise spectral density \({E_b}/{N_0}\) in low SNR regime by spreading differentially encoded information symbols along OFDM sub-carriers. We investigate the impact of spreading on bit-error rate (BER) and throughput under relative mobility and multipath fading scenarios. In order to maximize the throughput of the proposed method, we also optimize spreading factor and modulation order. The simulation results demonstrate significant BER and throughput performance gain as compared to prevailing differential encoding methods.     

Performance analysis of HARQ protocols with link adaptation on fading channels

This work considers hybrid automatic repeat request (HARQ) protocols on a fading channel with Chase combining and deals with both Rayleigh and Nakagami-m fading. We derive the packet loss probability and the throughput for HARQ both for a slow-varying and a fast-varying channel. We then consider link adaptation with complete channel state information (CSI) for which the instantaneous signal-to-noise ratio (SNR) is known and with incomplete CSI for which only the average SNR is known. We derive analytical formulae of the long-term throughput. These formulae are simple enough to be used for higher level simulations. We show that the throughput is slightly higher on a slow-varying channel but at the expense of a higher loss probability.     

Adaptive source rate control for real‐time wireless video transmission

Hybrid ARQ schemes can yield much better throughput and reliability than static FEC schemes for the transmission of data over time-varying wireless channels. However these schemes result in extra delay. They adapt to the varying channel conditions by retransmitting erroneous packets, this causes variable effective data rates for current PCS networks because the channel bandwidth is constant. Hybrid ARQ schemes are currently being proposed as the error control schemes for real-time video transmission. An important issue is how to ensure low delay while taking advantage of the high throughput and reliability that these schemes provide for. In this paper we propose an adaptive source rate control (ASRC) scheme which can work together with the hybrid ARQ error control schemes to achieve efficient transmission of real-time video with low delay and high reliability. The ASRC scheme adjusts the source rate based on the channel conditions, the transport buffer occupancy and the delay constraints. It achieves good video quality by dynamically changing both the number of the forced update (intracoded) macroblocks and the quantization scale used in a frame. The number of the forced update macroblocks used in a frame is first adjusted according to the allocated source rate. This reduces the fluctuation of the quantization scale with the change in the channel conditions during encoding so that the uniformity of the video quality is improved. The simulation results show that the proposed ASRC scheme performs very well for both slow fading and fast fading channels. This revised version was published online in July 2006 with corrections to the Cover Date.     

Statistical decision making in adaptive modulation and coding for 3G wireless systems

In this paper, we address the application of adaptive modulation and coding (AMC) for 3rd-generation (3G) wireless systems. We propose a new method for selecting the appropriate modulation and coding schemes (MCS) according to the estimated channel condition. In this method, we take a statistical decision making approach to maximize the average throughput while maintaining an acceptable frame error rate (FER). We use a first order finite state Markov model to approximate the time variations of the average channel signal to noise ratio (SNR) in subsequent frames. The MCS is selected in each state of this Markov model (among the choices proposed in the 3G standards proposals) to maximize the statistical average of the throughput in that state. Using this decision making approach, we also propose a simplified Markov model with fewer parameters, which is suitable in systems where changes in the fading characteristics need to be accounted for in an adaptive fashion. Numerical results are presented showing that both of our models substantially outperform the conventional techniques that use a memoryless threshold based decision making.     

DCNC: throughput maximization via delay controlled network coding for wireless mesh networks

Network coding (NC) can greatly improve the performance of wireless mesh networks (WMNs) in terms of throughput and reliability, and so on. However, NC generally performs a batch‐based transmission scheme, the main drawback of this scheme is the inevitable increase in average packet delay, that is, a large batch size may achieve higher throughput but also induce larger average packet delay. In this work, we put our focus on the tradeoff between the average throughput and packet delay; in particular, our ultimate goal is to maximize the throughput for real‐time traffic under the premise of diversified and time‐varying delay requirements. To tackle this problem, we propose DCNC, a delay controlled network coding protocol, which can improve the throughput for real‐time traffic by dynamically controlling the delay in WMNs. To define an appropriate control foundation, we first build up a delay prediction model to capture the relationship between the average packet delay and the encoding batch size. Then, we design a novel freedom‐based feedback scheme to efficiently reflect the reception of receivers in a reliable way. Based on the predicted delay and current reception status, DCNC utilizes the continuous encoding batch size adjustment to control delay and further improve the throughput. Extensive simulations show that, when faced with the diversified and time‐varying delay requirements, DCNC can constantly fulfill the delay requirements, for example, achieving over 95% efficient packet delivery ratio (EPDR) in all instances under good channel quality, and also obtains higher throughput than the state‐of‐art protocol. Copyright © 2014 John Wiley & Sons, Ltd.     

Queue length aware power control for delay‐ constrained communication over fading channels

In this paper, we study efficient power control schemes for delay sensitive communication over fading channels. Our objective is to find a power control law that optimizes the link layer performance, specifically, minimizes the packet drop probability, subject to a long‐term average power constraint. We assume the buffer at the transmitter is finite; hence packet drop happens when the buffer is full. The fading channel under our study has a continuous state, e.g., Rayleigh fading. Since the channel state space is continuous, dynamic programming is not applicable for power control. In this paper, we propose a sub‐optimal power control law based on a parametric approach. The proposed power control scheme tries to minimize the packet drop probability by considering the queue length, i.e., reducing the probability of those queue‐length states that will cause full buffer. Simulation results show that our proposed power control scheme reduces the packet drop probability by one or two orders of magnitude, compared to the time domain water filling (TDWF) and the truncated channel inversion (TCI) power control. Copyright © 2010 John Wiley & Sons, Ltd.     

On the Performance of FFT/DWT/DCT-based OFDM Systems with Chaotic Interleaving and Channel Estimation Algorithms

The efficiency of data transmission over fading channels in orthogonal frequency division multiplexing (OFDM) systems depends on the employed interleaving method. In this study, we propose an improved chaotic interleaving scheme which aims to improve the performance of OFDM system under fading channel. In the proposed scheme, the binary data is interleaved with chaotic Baker map prior to the modulation process. In the sequel, significant degree of encryption is being added during data transmission. The performance of the proposed approach is tested on the conventional fast Fourier transform OFDM, discrete wavelet transform OFDM, and discrete cosine transform OFDM with and without chaotic interleaving. Furthermore, an expectation–maximization (EM) algorithm is proposed for improving channel impulse response (CIR) estimation based on a maximum likelihood principle. The proposed scheme makes use of EM algorithm to update the channel estimates until convergence is reached. The simulation results show the efficiency of the proposed algorithms under Rayleigh fading environments where the symbol error rate essentially coincides with that of the perfect channel case after the fifth EM iteration.     

Adaptive transmission with finite code rates

This work examines a transmission system which adapts a finite set of code rates and a continuously varying transmit power. We propose a technique for finding the average reliable throughput (ART)-maximizing policy satisfying an average power constraint for a slow fading additive white Gaussian noise (AWGN) channel. ART is a measure motivated by the information outage and can, for example, be argued to characterize the long-term average throughput of a data packet transmission system with a transmit queue and a feedback protocol which requests retransmission of erroneously received packets. Given the size of the code rate set L, the ART-maximizing policy has the following properties. 1. For a given set of code rates, the optimum allocation policy suggests quantizing the fading state space into a set of L+1 corresponding intervals. For each quantization interval the optimal policy specifies a minimum transmitted power assignment which guarantees zero information outage. The optimum average power assignments across quantization intervals have a waterfilling relationship with respect to the interval channel quality measure. 2. The joint optimization of quantization intervals and the corresponding rate assignments are shown to have multiple local maxima. Nevertheless, this optimization problem can be reduced to a simple one-dimensional search over a parameter which determines the outage interval. Numerical results show that, in a Rayleigh-fading channel, there is only a 1-dB gap between the ergodic capacity and the throughput of a two-rate adaptive transmission system when the throughput is less than 6 bits/s/Hz. A special case of our optimal policy assignment is the optimal power and rate policy for an adaptive M-QAM system.