arXiv subjects

He Chen

Publications and source records attributed to He Chen.

At least 91 records · Page 5Linked to original sources

arXiv2020

Minimizing Age of Information via Hybrid NOMA/OMA

This paper considers a wireless network with a base station (BS) conducting timely transmission to two clients in a slotted manner via hybrid non-orthogonal multiple access (NOMA)/orthogonal multiple access (OMA). Specifically, the BS is able to adaptively switch between NOMA and OMA for the downlink transmission to minimize the information freshness, characterized by Age of Information (AoI), of the network. If the BS chooses OMA, it can only serve one client within a time slot and should decide which client to serve; if the BS chooses NOMA, it can serve both clients simultaneously and should decide the power allocated to each client. To minimize the weighted sum of expected AoI of the network, we formulate a Markov Decision Process (MDP) problem and develop an optimal policy for the BS to decide whether to use NOMA or OMA for each downlink transmission based on the instantaneous AoI of both clients. We prove the existence of optimal stationary and deterministic policy, and perform action elimination to reduce the action space for lower computation complexity. The optimal policy is shown to have a switching-type property with obvious decision switching boundaries. A suboptimal policy with lower computation complexity is also devised, which can achieve near-optimal performance according to our simulation results. The performance of different policies under different system settings is compared and analyzed in numerical results to provide useful insights for practical system designs.

cs.IT↗

arXiv2020

Age-Oriented Opportunistic Relaying in Cooperative Status Update Systems with Stochastic Arrivals

This paper considers a cooperative status update system with a source aiming to send randomly generated status updates to a designated destination as timely as possible with the help of a relay. We adopt a recently proposed concept, Age of Information (AoI), to characterize the timeliness of the status updates. We propose an age-oriented opportunistic relaying (AoR) protocol to reduce the AoI of the considered system. Specifically, the relay opportunistically replaces the source to retransmit the successfully received status updates that have not been correctly delivered to the destination, but the retransmission of the relay can be preempted by the arrival of a new status update at the source. By carefully analyzing the evolution of AoI, we derive a closed-form expression of the average AoI for the proposed AoR protocol. We further minimize the average AoI by optimizing the generation probability of the status updates at the source. Simulation results validate our theoretical analysis and demonstrate that the average AoI performance of the proposed AoR protocol is superior to that of the non-cooperative system.

cs.IT↗

arXiv2020

Minimizing the Age of Information of Cognitive Radio-Based IoT Systems Under A Collision Constraint

This paper considers a cognitive radio-based IoT monitoring system, consisting of an IoT device that aims to update its measurement to a destination using cognitive radio technique. Specifically, the IoT device as a secondary user (SIoT), seeks and exploits the spectrum opportunities of the licensed band vacated by its primary user (PU) to deliver status updates without causing visible effects to the licensed operation. In this context, the SIoT should carefully make use of the licensed band and schedule when to transmit to maintain the timeliness of the status update. We adopt a recent metric, Age of Information (AoI), to characterize the timeliness of the status update of the SIoT. We aim to minimize the long-term average AoI of the SIoT while satisfying the collision constraint imposed by the PU by formulating a constrained Markov decision process (CMDP) problem. We first prove the existence of optimal stationary policy of the CMDP problem. The optimal stationary policy (termed age-optimal policy) is shown to be a randomized simple policy that randomizes between two deterministic policies with a fixed probability. We prove that the two deterministic policies have a threshold structure and further derive the closed-form expression of average AoI and collision probability for the deterministic threshold-structured policy by conducting Markov Chain analysis. The analytical expression offers an efficient way to calculate the threshold and randomization probability to form the age-optimal policy. For comparison, we also consider the throughput maximization policy (termed throughput-optimal policy) and analyze the average AoI performance under the throughput-optimal policy in the considered system. Numerical simulations show the superiority of the derived age-optimal policy over the throughput-optimal policy. We also unveil the impacts of various system parameters on the corresponding optimal policy and the resultant average AoI.

cs.IT↗

arXiv2019

Signal Design for AF Relay Systems using Superposition Coding and Finite-Alphabet Inputs

This paper focuses on the signal design in a Gaussian amplify-and-forward (AF) relay system with superposition coding (SC) being applied at the relay, which allows the source and relay to transmit their own information within two time slots. Practical quadrature amplitude modulation (QAM) constellations are adopted at the source and relay. To improve the system error performance, we optimize the weight coefficients adopted at the source and relay to maximize the minimum Euclidean distance of the received composite constellation, subject to their individual average power constraints. The formulated optimization problem is shown to be a mixed continuous-discrete one that is non-trivial to resolve in general. By resorting to the punched Farey sequence, we manage to obtain the optimal solution to the formulated problem by first partitioning the entire feasible region into a finite number of sub-intervals and then taking the maximum over all the possible sub-intervals. Simulation results are provided to demonstrate the superior performance of our proposed design based on SC over that using conventional time division multiple access (TDMA).

eess.SP↗

arXiv2019

Minimizing Age of Information for Real-Time Monitoring in Resource-Constrained Industrial IoT Networks

This paper considers an Industrial Internet of Thing (IIoT) system with a source monitoring a dynamic process with randomly generated status updates. The status updates are sent to an designated destination in a real-time manner over an unreliable link. The source is subject to a practical constraint of limited average transmission power. Thus, the system should carefully schedule when to transmit a fresh status update or retransmit the stale one. To characterize the performance of timely status update, we adopt a recent concept, Age of Information (AoI), as the performance metric. We aim to minimize the long-term average AoI under the limited average transmission power at the source, by formulating a constrained Markov Decision Process (CMDP) problem. To address the formulated CMDP, we recast it into an unconstrained Markov Decision Process (MDP) through Lagrangian relaxation. We prove the existence of optimal stationary policy of the original CMDP, which is a randomized mixture of two deterministic stationary policies of the unconstrained MDP. We also explore the characteristics of the problem to reduce the action space of each state to significantly reduce the computation complexity. We further prove the threshold structure of the optimal deterministic policy for the unconstrained MDP. Simulation results show the proposed optimal policy achieves lower average AoI compared with random policy, especially when the system suffers from stricter resource constraint. Besides, the influence of status generation probability and transmission failure rate on optimal policy and the resultant average AoI as well as the impact of average transmission power on the minimal average AoI are unveiled.

cs.IT↗

arXiv2019

Minimizing Age of Information in Cognitive Radio-based IoT Systems: Underlay or Overlay?

We consider a cognitive radio-based Internet-of-Things (CR-IoT) network consisting of one primary IoT (PIoT) system and one secondary IoT (SIoT) system. The IoT devices of both the PIoT and the SIoT respectively monitor one physical process and send randomly generated status updates to their associated access points (APs). The timeliness of the status updates is important as the systems are interested in the latest condition (e.g., temperature, speed and position) of the IoT device. In this context, two natural questions arise: (1) How to characterize the timeliness of the status updates in CR-IoT systems? (2) Which scheme, overlay or underlay, is better in terms of the timeliness of the status updates. To answer these two questions, we adopt a new performance metric, named the age of information (AoI). We analyze the average peak AoI of the PIoT and the SIoT for overlay and underlay schemes, respectively. Simple asymptotic expressions of the average peak AoI are also derived when the PIoT operates at high signal-to-noise ratio (SNR). Based on the asymptotic expressions, we characterize a critical generation rate of the PIoT system, which can determine the superiority of overlay and underlay schemes in terms of the average peak AoI of the SIoT. Numerical results validate the theoretical analysis and uncover that the overlay and underlay schemes can outperform each other in terms of the average peak AoI of the SIoT for different system setups.

eess.SP↗

arXiv2019

On the Age of Information of Short-Packet Communications with Packet Management

In this paper, we consider a point-to-point wireless communication system. The source monitors a physical process and generates status update packets according to a Poisson process. The packets are transmitted to the destination by using finite blocklength coding to update the status (e.g., temperature, speed, position) of the monitored process. In some applications, such as real-time monitoring and tracking, the timeliness of the status updates is critical since the users are interested in the latest condition of the process. The timeliness of the status updates can be reflected by a recently proposed metric, termed the age of information (AoI). We focus on the packet management policies for the considered system. Specifically, the preemption and discard of status updates are important to decrease the AoI. For example, it is meaningless to transmit stale status updates when a new status update is generated. We propose three packet management schemes in the transmission between the source and the destination, namely non-preemption (NP), preemption (PR) and retransmission (RT) schemes. We derive closed-form expressions of the average AoI for the proposed three schemes. Based on the derived analytical expressions of the average AoI, we further minimize the average AoI by optimizing the packet blocklength for each status update. Simulation results are provided to validate our theoretical analysis, which further show that the proposed schemes can outperform each other for different system setups, and the proposed schemes considerably outperform the existing ones without packet management at medium to high generation rate.

eess.SP↗

arXiv2019

Beam Allocation for Millimeter-Wave MIMO Tracking Systems

In this paper, we propose a new beam allocation strategy aiming to maximize the average successful tracking probability (ASTP) of time-varying millimeter-wave MIMO systems. In contrast to most existing works that employ one transmitting-receiving (Tx-Rx) beam pair once only in each training period, we investigate a more general framework, where the Tx-Rx beam pairs are allowed to be used repeatedly to improve the received signal powers in specific directions. In the case of orthogonal Tx-Rx beam pairs, a power-based estimator is employed to track the time-varying AoA and AoD of the channel, and the resulting training beam pair sequence design problem is formulated as an integer nonlinear programming (I-NLP) problem. By dividing the feasible region into a set of subregions, the formulated I-NLP is decomposed into a series of concave sub I-NLPs, which can be solved by recursively invoking a nonlinear branch-and-bound algorithm. To reduce the computational cost, we relax the integer constraints of each sub I-NLP and obtain a low-complexity solution via solving the Karush-Kuhn-Tucker conditions of their relaxed problems. For the case when the Tx-Rx beam pairs are overlapped in the angular space, we estimate the updated AoA and AoD via an orthogonal matching pursuit (OMP) algorithm. Moreover, since no explicit expression for the ASTP exists for the OMP-based estimator, we derive a closed-form lower bound of the ASTP, based on which a favorable beam pair allocation strategy can be obtained. Numerical results demonstrate the superiority of the proposed beam allocation strategy over existing benchmarks.

eess.SP↗

arXiv2019

Curvature: A signature for Action Recognition in Video Sequences

In this paper, a novel signature of human action recognition, namely the curvature of a video sequence, is introduced. In this way, the distribution of sequential data is modeled, which enables few-shot learning. Instead of depending on recognizing features within images, our algorithm views actions as sequences on the universal time scale across a whole sequence of images. The video sequence, viewed as a curve in pixel space, is aligned by reparameterization using the arclength of the curve in pixel space. Once such curvatures are obtained, statistical indexes are extracted and fed into a learning-based classifier. Overall, our method is simple but powerful. Preliminary experimental results show that our method is effective and achieves state-of-the-art performance in video-based human action recognition. Moreover, we see latent capacity in transferring this idea into other sequence-based recognition applications such as speech recognition, machine translation, and text generation.

cs.CV↗

arXiv2019

Noncoherent Multiuser Massive SIMO for Low-Latency Industrial IoT Communications

In this paper, we consider a multiuser massive single-input multiple-output (SIMO) enabled Industrial Internet of Things (IIoT) communication system. To reduce the latency and overhead caused by channel estimation, we assume that only the large-scale fading coefficients are available. We employ a noncoherent maximum-likelihood (ML) detector at the receiver side which does not need the instantaneous channel state information (CSI). For such a massive SIMO system, we present a new design framework to assure that each transmitted signal matrix can be uniquely determined in the noise-free case and be reliably estimated in noisy cases. The key idea is to utilize a new concept called the uniquely decomposable constellation group (UDCG) based on the practically used quadrature amplitude modulation~(QAM) constellation. To improve the average error performance when the antenna array size is scaled up, we propose a max-min Kullback-Leibler (KL) distance design by carrying out optimization over the transmitted power and the sub-constellation assignment. Finally, simulation results show that the proposed design outperforms significantly the existing max-min Euclidean distance based method in terms of error performance. Moreover, our proposed approach also has a better error performance than the conventional coherent zero-forcing (ZF) receiver with orthogonal training for cell edge users.

cs.IT↗

arXiv2019

Noncoherent and Non-orthogonal Massive SIMO for Critical Industrial IoT Communications

Towards the realization of ultra-reliable low-latency wireless communications required in critical industrial Internet of Things (IIoT) applications, this paper presents a new noncoherent and non-orthogonal massive single-input multiple-output (SIMO) framework, in which a large number of antennas are deployed to provide high spatial diversity so as to enable ultra-reliable communications, and noncoherent transmission and non-orthogonal multiple access techniques are applied to effectively reduce the latency at the physical and data link layers, respectively. A two-user IIoT system is considered to elaborate the key design principle of our framework, in which two controlled nodes (CNs) transmit their data to a common managing node (MN) on the same time-frequency resource block, and the MN implements the noncoherent maximum likelihood detector to recover the transmitted symbols of both CNs from the received sum signal. We analyze the error performance of the considered system and then minimize the system error probability by jointly designing the constellations of both CNs. Simulation results show that our design has lower error probability than existing designs.

cs.IT↗

arXiv2019

Average SEP-Optimal Precoding for Correlated Massive MIMO with ZF Detection: An Asymptotic Analysis

This paper investigates the symbol error probability~(SEP) of point-to-point massive multiple-input multiple-output (MIMO) systems using equally likely PAM, PSK, and square QAM signallings in the presence of transmitter correlation. The receiver has perfect knowledge of the channel coefficients, while the transmitter only knows first- and second-order channel statistics. With a zero-forcing~(ZF) detector implemented at the receiver side, we design and derive closed-form expressions of the optimal precoders at the transmitter that minimizes the average SEP over channel statistics for various modulation schemes. We then unveil some nice structures on the resulting minimum average SEP expressions, which naturally motivate us to explore the use of two useful mathematical tools to systematically study their asymptotic behaviors. The first tool is the Szegö's theorem on large Hermitian Toeplitz matrices and the second tool is the well-known limit: $\lim_{x\to\infty}(1+1/x)^x=e$. The application of these two tools enables us to attain very simple expressions of the SEP limits as the number of the transmitter antennas goes to infinity. A major advantage of our asymptotic analysis is that the asymptotic SEP converges to the true SEP when the number of antennas is moderately large. As such, the obtained expressions can serve as effective SEP approximations for massive MIMO systems even when the number of antennas is not very large. For the widely used exponential correlation model, we derive closed-form expressions for the SEP limits of both optimally precoded and uniformly precoded systems. Extensive simulations are provided to demonstrate the effectiveness of our asymptotic analysis and compare the performance limit of optimally precoded and uniformly precoded systems.

cs.IT↗

arXiv2018

Ultra-Reliable Low Latency Cellular Networks: Use Cases, Challenges and Approaches

The fifth-generation cellular mobile networks are expected to support mission critical ultra-reliable low latency communication (URLLC) services in addition to the enhanced mobile broadband applications. This article first introduces three emerging mission critical applications of URLLC and identifies their requirements on end-to-end latency and reliability. We then investigate the various sources of end-to-end delay of current wireless networks by taking the 4G Long Term Evolution (LTE) as an example. Subsequently, we propose and evaluate several techniques to reduce the end-to-end latency from the perspectives of error control coding, signal processing, and radio resource management. We also briefly discuss other network design approaches with the potential for further latency reduction.

cs.IT↗

arXiv2018

Ray-of-Arrival Passing for Indirect Beam Training in Cooperative Millimeter Wave MIMO Networks

This paper is concerned with the channel estimation problem in multi-cell Millimeter (mmWave) wireless systems. We develop a novel Ray-of-Arrival Passing for Indirect (RAPID) Beam Training framework, in which a network consisting of multiple BS are able to work cooperatively to estimate jointly the UE channels. To achieve this aim, we consider the spatial geometry of the mmWave environment and transform conventional angular domain beamforming concepts into the more euclidean, Ray-based domain. Leveraging this model, we then consider the conditional probabilities that pilot signals are received in each direction, given that the deployment of each BS is known to the network. Simulation results show that RAPID is able to improve the average estimation of the network and significantly increase the rate of poorer quality links. Furthermore, we also show that, when a coverage rate threshold is considered, RAPID is able to improve greatly the probability that multiple link options will be available to a user at any given time.

cs.IT↗

arXiv2018

Beam-On-Graph: Simultaneous Channel Estimation for mmWave MIMO Systems with Multiple Users

This paper is concerned with the channel estimation problem in multi-user millimeter wave (mmWave) wireless systems with large antenna arrays. We develop a novel simultaneous-estimation with iterative fountain training (SWIFT) framework, in which multiple users estimate their channels at the same time and the required number of channel measurements is adapted to various channel conditions of different users. To achieve this, we represent the beam direction estimation process by a graph, referred to as the beam-on-graph, and associate the channel estimation process with a code-on-graph decoding problem. Specifically, the base station (BS) and each user measure the channel with a series of random combinations of transmit/receive beamforming vectors until the channel estimate converges. As the proposed SWIFT does not adapt the BS's beams to any single user, we are able to estimate all user channels simultaneously. Simulation results show that SWIFT can significantly outperform the existing random beamforming-based approaches, which use a predetermined number of measurements, over a wide range of signal-to-noise ratios and channel coherence time. Furthermore, by utilizing the users' order in terms of completing their channel estimation, our SWIFT framework can infer the sequence of users' channel quality and perform effective user scheduling to achieve superior performance.

cs.IT↗

arXiv2018

Construction and Performance of Quantum Burst Error Correction Codes for Correlated Errors

In practical communication and computation systems, errors occur predominantly in adjacent positions rather than in a random manner. In this paper, we develop a stabilizer formalism for quantum burst error correction codes (QBECC) to combat such error patterns in the quantum regime. Our contributions are as follows. Firstly, we derive an upper bound for the correctable burst errors of QBECCs, the quantum Reiger bound (QRB). This bound generalizes the quantum Singleton bound for standard quantum error correction codes (QECCs). Secondly, we propose two constructions of QBECCs: one by heuristic computer search and the other by concatenating two quantum tensor product codes (QTPCs). We obtain several new QBECCs with better parameters than existing codes with the same coding length. Moreover, some of the constructed codes can saturate the quantum Reiger bounds. Finally, we perform numerical experiments for our constructed codes over Markovian correlated depolarizing quantum memory channels, and show that QBECCs indeed outperform standard QECCs in this scenario.

cs.IT↗

arXiv2018

Accumulate Then Transmit: Multi-user Scheduling in Full-Duplex Wireless-Powered IoT Systems

This paper develops and evaluates an accumulate-then-transmit framework for multi-user scheduling in a full-duplex (FD) wireless-powered Internet-of-Things system, consisting of multiple energy harvesting (EH) IoT devices (IoDs) and one FD hybrid access point (HAP). All IoDs have no embedded energy supply and thus need to perform EH before transmitting their data to the HAP. Thanks to its FD capability, the HAP can simultaneously receive data uplink and broadcast energy-bearing signals downlink to charge IoDs. The instantaneous channel information is assumed unavailable throughout this paper. To maximize the system average throughput, we design a new throughput-oriented scheduling scheme, in which a single IoD with the maximum weighted residual energy is selected to transmit information to the HAP, while the other IoDs harvest and accumulate energy from the signals broadcast by the HAP. However, similar to most of the existing throughput-oriented schemes, the proposed throughout-oriented scheme also leads to unfair inter-user throughput because IoDs with better channel performance will be granted more transmission opportunities. To strike a balance between the system throughput and user fairness, we then propose a fairness-oriented scheduling scheme based on the normalized accumulated energy. To evaluate the system performance, we model the dynamic charging/discharging processes of each IoD as a finite-state Markov Chain. Analytical expressions of the system outage probability and average throughput are derived over Rician fading channels for both proposed schemes. Simulation results validate the performance analysis and demonstrate the performance superiority of both proposed schemes over the existing schemes.

cs.IT↗

arXiv2017

Incentive Mechanism Design for Wireless Energy Harvesting-Based Internet of Things

Radio frequency energy harvesting (RFEH) is a promising technology to charge unattended Internet of Things (IoT) low-power devices remotely. To enable this, in future IoT system, besides the traditional data access points (DAPs) for collecting data, energy access points (EAPs) should be deployed to charge IoT devices to maintain their sustainable operations. Practically, the DAPs and EAPs may be operated by different operators, and the DAPs thus need to provide effective incentives to motivate the surrounding EAPs to charge their associated IoT devices. Different from existing incentive schemes, we consider a practical scenario with asymmetric information, where the DAP is not aware of the channel conditions and energy costs of the EAPs. We first extend the existing Stackelberg game-based approach with complete information to the asymmetric information scenario, where the expected utility of the DAP is defined and maximized. To deal with asymmetric information more efficiently, we then develop a contract theory-based framework, where the optimal contract is derived to maximize the DAP's expected utility as well as the social welfare. Simulations show that information asymmetry leads to severe performance degradation for the Stackelberg game-based framework, while the proposed contract theory-based approach using asymmetric information outperforms the Stackelberg game-based method with complete information. This reveals that the performance of the considered system depends largely on the market structure (i.e., whether the EAPs are allowed to optimize their received power at the IoT devices with full freedom or not) than on the information availability (i.e., the complete or asymmetric information).

cs.IT↗