State Radio Regulation Of China

Wireless signal recognition plays an important role in cognitive radio, which promises a broad prospect in spectrum monitoring and management with the coming applications for the 5G and Internet of Things networks. Therefore, a great deal of research and exploration on signal recognition has been done and a series of effective schemes has been developed. In this paper, a brief overview of signal recognition approaches is presented. More specifically, classical methods, emerging machine learning, and deep leaning schemes are extended from modulation recognition to wireless technology recognition with the continuous evolution of wireless communication system. In addition, the opening problems and new challenges in practice are discussed. Finally, a conclusion of existing methods and future trends on signal recognition is given.

This paper investigates energy-efficient device-to-device (D2D) communications in cellular networks. We aim to maximize the overall energy-efficiency (EE) of D2D users and regular cellular users (RCUs) while considering the circuit power consumption and the quality-of-service (QoS) requirements for both types of users as well as power constraints. Three transmission modes, namely, dedicated mode, reusing mode, and cellular mode, are considered for D2D users to share spectrum with RCUs. Parametric Dinkelbach method and concave-convex procedure (CCCP) are adopted to transform the original optimization problems into more tractable forms through sequential convex approximations. Then, interior point method is exploited to obtain the optimal solution. Simulation results show that system EE can be improved significantly with the proposed mode switching algorithm compared with the single mode transmission. Besides, it is also shown that the reusing mode is more preferred in the EE based mode switching while it is the dedicated mode in the spectrum-efficiency (SE) based mode switching in most situations.

Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information. However, other performance requirements such as life cycle of nodes, stability and security are not set as primary design objectives. This makes data collection ability of vehicular nodes in real application environment inferior. By considering the features of nodes in wireless IoV, such as large scales of deployment, volatility and low time delay, an efficient data collection algorithm is proposed for mobile vehicle network environment. An adaptive sensing model is designed to establish vehicular data collection protocol. The protocol adopts group management in model communication. The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes. It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes. In addition, secure data collection between sensing nodes is undertaken as well. The simulation and experiments show that the vehicular node can realize secure and real-time data collection. Moreover, the proposed algorithm is superior in vehicular network life cycle, power consumption and reliability of data collection by comparing to other algorithms.

The temperature of electrolytic capacitor in light-emitting diode (LED) drivers continuously increases under operation conditions, thus the capacitors degrade faster than that with constant temperature assumption. In this paper, a physics-of-failure (PoF)-based reliability prediction methodology is developed for LED drivers to consider the temperature change of electrolytic capacitor. SPICE simulation, compact thermal modeling, and Monte Carlo simulation are integrated to predict the failure rate distribution of an electrolytic capacitor of given LED driver systems. The simulation results agree well with the accelerated test results for an RC linear AC-DC converter. Furthermore, a single inductor buck-boost DC-DC converter is simulated to understand the degradation behavior of electrolytic capacitor. It has been found that the temperature of an output stage capacitor increases significantly during operation time. The capacitor's performance without taking temperature change into account results in an overestimated driver lifetime by more than 38% for the selected case study.

User-perceived performance continues to be the most important QoS indicator in cloud-based data centers today. Effective allocation of virtual machines (VMs) to handle both CPU intensive and I/O intensive workloads is a crucial performance management capability in virtualized clouds. Although a fair amount of researches have dedicated to measuring and scheduling jobs among VMs, there still lacks of in-depth understanding of performance factors that impact the efficiency and effectiveness of resource multiplexing and scheduling among VMs. In this paper, we present the experimental research on performance interference in parallel processing of CPU-intensive and network-intensive workloads on Xen virtual machine monitor (VMM). Based on our study, we conclude with five key findings which are critical for effective performance management and tuning in virtualized clouds. First, colocating network-intensive workloads in isolated VMs incurs high overheads of switches and events in Dom0 and VMM. Second, colocating CPU-intensive workloads in isolated VMs incurs high CPU contention due to fast I/O processing in I/O channel. Third, running CPU-intensive and network-intensive workloads in conjunction incurs the least resource contention, delivering higher aggregate performance. Fourth, performance of network-intensive workload is insensitive to CPU assignment among VMs, whereas adaptive CPU assignment among VMs is critical to CPU-intensive workload. The more CPUs pinned on Dom0 the worse performance is achieved by CPU-intensive workload. Last, due to fast I/O processing in I/O channel, limitation on grant table is a potential bottleneck in Xen. We argue that identifying the factors that impact the total demand of exchanged memory pages is important to the in-depth understanding of interference costs in Dom0 and VMM.

Exploiting millimeter wave is an effective way to meet the data traffic demand in the 5G wireless communication system. In this paper, we study secure transmissions under slow fading channels with multipath propagation in millimeter wave systems. Concerning the new propagation characteristics of millimeter wave, we investigate three transmission schemes, namely, maximum ratio transmitting (MRT) beamforming, artificial noise (AN) beamforming, and partial MRT (PMRT) beamforming. We evaluate the secrecy performance by analyzing both the secrecy outage probability (SOP) and the secrecy throughput for each scheme. Particularly, for the AN scheme, we derive a closed-form expression for the optimal power allocation ratio of the information signal power to the total transmit power that minimizes the SOP, as well as obtain an explicit solution on the optimal transmission parameters that maximize the secrecy throughput. By comparing the secrecy performances achieved by different strategies, we demonstrate that the secrecy performance of the millimeter wave system is significantly influenced by the relationship between the legitimate user's and the eavesdropper's spatially resolvable paths, which is different from the wireless systems with statistically independent channel models. In the absence of the common path between the legitimate user and the eavesdropper, MRT beamforming is the best scheme. In the presence of common paths, AN beamforming and PMRT beamforming show their respective superiorities depending on the transmit power and the number of common paths. Numerical results are provided to verify our theoretical analysis.

With a considerable ratio of the world's mobile users, China has been actively promoting research on 5G, in which the spectrum issue is of great interest. New 5G characteristics put forward a lot of requirements for spectrum in terms of total amount, candidate bands, as well as new challenges for spectrum usage methods and management. Based on China's current situation, this article first discusses the 5G vision, spectrum demands, and potential candidate bands. Furthermore, it is indicated that spectrum sharing will bring many benefits for 5G systems, and different sharing scenarios are summarized. Finally, based on the current framework of spectrum management in China, potential services classification and spectrum assessment are proposed to accommodate new 5G requirements.

Cognitive radios may operate in practice under various adverse environments. For typical mobile and short-range scenarios, wireless links may tend to be time and frequency selective, i.e., the multipath propagations with time-varying fading coefficients will be inevitable. To cope with the encountered doubly-selective channels, in this paper we present a new spectrum sensing algorithm for distributed applications. First, a dynamic discrete state-space model is established to characterize sensing process, where the occupancy state of primary band and the time-varying multipath channel are treated as two hidden states, while the summed energy is adopted as the observed output. With this new paradigm, spectrum sensing is realized by acquiring primary states and time-dependent multipath channel jointly. For the formulated problem, unfortunately, Bayesian statistical inference may be impractical due to the absence of likelihoods and involved non-stationary distributions. To remedy this problem, an iterative algorithm is further designed by resorting to sequential importance sampling techniques; thus, the dynamic non-Gaussian multipath channel and primary states are estimated recursively. Another critical challenge, e.g., the noise uncertainty, is also considered, which may be incorporated conveniently into this sensing diagram and, furthermore, addressed effectively by the designed algorithm. Simulations validate the proposed algorithm. While classical schemes fail to deal with doubly selective channels, the new sensing scheme can exploit the underlying channel memory and operate well, which provides a great promise to realistic applications.

The Internet of Vehicles (IoV) has been widely researched in recent years, and cloud computing has been one of the key technologies in the IoV. Although cloud computing provides high performance compute, storage and networking services, the IoV still suffers with high processing latency, less mobility support and location awareness. In this paper, we integrate fog computing and software defined networking (SDN) to address those problems. Fog computing extends computing and storing to the edge of the network, which could decrease latency remarkably in addition to enable mobility support and location awareness. Meanwhile, SDN provides flexible centralized control and global knowledge to the network. In order to apply the software defined cloud/ fog networking (SDCFN) architecture in the IoV effectively, we propose a novel SDN-based modified constrained optimization particle swarm optimization (MPSO-CO) algorithm which uses the reverse of the flight of mutation particles and linear decrease inertia weight to enhance the performance of constrained optimization particle swarm optimization (PSO-CO). The simulation results indicate that the SDN-based MPSO-CO algorithm could effectively decrease the latency and improve the quality of service (QoS) in the SDCFN architecture.

Server consolidation and application consolidation through virtualization are key performance optimizations in cloud-based service delivery industry. In this paper, we argue that it is important for both cloud consumers and cloud providers to understand the various factors that may have significant impact on the performance of applications running in a virtualized cloud. This paper presents an extensive performance study of network I/O workloads in a virtualized cloud environment. We first show that current implementation of virtual machine monitor (VMM) does not provide sufficient performance isolation to guarantee the effectiveness of resource sharing across multiple virtual machine instances (VMs) running on a single physical host machine, especially when applications running on neighboring VMs are competing for computing and communication resources. Then we study a set of representative workloads in cloud-based data centers, which compete for either CPU or network I/O resources, and present the detailed analysis on different factors that can impact the throughput performance and resource sharing effectiveness. For example, we analyze the cost and the benefit of running idle VM instances on a physical host where some applications are hosted concurrently. We also present an in-depth discussion on the performance impact of colocating applications that compete for either CPU or network I/O resources. Finally, we analyze the impact of different CPU resource scheduling strategies and different workload rates on the performance of applications running on different VMs hosted by the same physical machine.

Mm-wave offers a sensible solution to the capacity crunch faced by 5G wireless communications. This paper comprehensively studies physical layer security in a multi-input single-output mm-wave system, where multiple single-antenna eavesdroppers are randomly located. Concerning the specific propagation characteristics of mm-wave, we investigate two secure transmission schemes, namely maximum ratio transmitting beamforming and artificial noise (AN) beamforming. Specifically, we first derive closed-form expressions of the connection probability for both schemes. We then analyze the secrecy outage probability in both non-colluding eavesdroppers and colluding eavesdroppers scenarios. Also, we maximize the secrecy throughput under a secrecy outage probability constraint, and obtain optimal transmission parameters, especially the power allocation between AN and the information signal for AN beamforming. Numerical results are provided to verify our theoretical analysis. We observe that the density of eavesdroppers, the spatially resolvable paths of the destination and eavesdroppers all contribute to the secrecy performance and the parameter design of mm-wave systems.

More and more mid-power white-light LED (MP LED) solutions have been used in outdoor illumination due to their good performance, cost attractiveness, and low energy consumption as compared with conventional lighting solutions. Hence, there is a need for MP LED manufacturers to develop more robust MP LEDs aimed at outdoor applications but still offer a significant cost benefit as compared with currently widely used high-power LEDs. This implies that MP LEDs would be operated in an environment with high humidity and high temperature. This may lead to serious degradation with different failure modes compared with an indoor operation. However, the combined effect of temperature and humidity on the MP LED reliability has not been extensively studied in literature. In this paper, MP LEDs were studied by the wet high-temperature operation life (WHTOL) test in order to understand their degradation mechanisms due to the combined effect of temperature and humidity. It is found that encapsulant discoloration (yellowing) is the major degradation mechanism in the WHTOL test, which will induce serious lumen degradation and color shift. Furthermore, it has been found that electrical degradation in terms of forward voltage increase will also affect the lumen maintenance. Finally, statistical analysis shows that lumen degradation mechanisms in the WHTOL test are similar to a failure in the LM-80-08 test, demonstrating that the WHTOL test is an efficient accelerated degradation test method, which dramatically reduces the test duration compared with the LM-80-08 test.

In device-to-device (D2D) communications, channel state information (CSI) is exploited to manage the interference between D2D users and regular cellular users (CUs) and improve system performance. However, obtaining the accurate CSI is usually difficult and causes high overhead, particularly when the links are not connected to the base station (BS), such as the links between regular CUs and D2D receivers (CU-D links). In this paper, we investigate the signaling overhead and performance tradeoff in D2D communications with channel uncertainty. To limit interference to regular CUs, we only allow the resource of a CU to be reused by, at most, one D2D pair. We also assume that only partial CSI of the CU-D links is available at the BS and develop two different strategies to deal with the channel uncertainty, namely, probabilistic and partial feedback schemes. We first derive a probability-based resource-allocation scheme by utilizing channel statistical characteristics to maximize the overall throughput of the CUs and admissible D2D pairs while guaranteeing their quality of service (QoS) in terms of signal-to-interference-plus-noise ratio (SINR) and outage probability, respectively. Then, we propose an efficient feedback scheme to reduce the overhead of CSI feedback while providing near-optimal performance. In addition, we propose a combined scheme to take advantages of both probabilistic and partial feedback schemes. It is shown by simulation that there exists an optimal threshold of the outage probability for probabilistic scheme while the partial feedback scheme is robust to the channel models. Furthermore, the combined scheme outperforms the probabilistic and the partial feedback schemes in terms of overall throughput.

Recently, 5G installation has been started globally. Different capabilities are in the consistent procedure, like ultrareliability, mass connectivity, and specific low latency. Though, 5G is insufficient to meet all the necessities of the future technology in 2030 and so on. Next generation information and communication technology is playing an important role in attraction of researchers, industries, and technical people. With respect to 5G networks, sixth‐generation (6G) CR networks are anticipated to familiarize innovative use cases and performance metrics, such as to offer worldwide coverage, cost efficiency, enhanced spectral, energy improved intelligence, and safety. To reach such requirements, upcoming 6G CRNs will trust novel empowering technologies. Innovative network architecture and transmission technologies and air interface are of excessive position, like multiple accesses, waveform design, multiantenna technologies, and channel coding schemes. (1) To content, the condition should be of worldwide coverage, there will be no limit on 6G to global CR communication networks that may require to be completed with broadcast networks, like satellite communication networks, therefore, attaining a sea integrated communication network. (2) The spectrums overall will be entirely travelled to the supplementary rise connection density data rates in optical frequency bands, millimeter wave (mmWave), sub‐6 GHz, and terahertz (THz). (3) To see big datasets created because of tremendously varied CR communication networks, antenna rush, diverse communication scenarios, new provision necessities, wide bandwidth, and 6G CRNs will allow an innovative variety of intelligent applications with the assistance of big data and AI technologies. (4) Need to improve network security when deploying 6G technology in CR networks. 6G is decentralized, intended, intelligent innovative, and distributed network. In this article, we studied a survey of current developments and upcoming trends. We studied the predicted applications, possible technologies, and security issues for 6G CR network communication. We also discussed predicted future key challenges in 6G.

A quad-polarization reconfigurable reflectarray (RA) antenna, which can work in horizontal polarization (HP), vertical polarization (VP), left-hand circular polarization (LHCP), and right-hand circular polarization (RHCP) modes with simultaneous large-angle beam-scanning capability, is designed and experimentally verified. Under the traditional view at the element level, at least 2-bit phases are required because a 90° phase shift step is needed for conversion from linear polarization (LP) to circular polarization (CP). In this work, we found that the extra phase shifts (90°/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$- 90^{\circ })$ </tex-math></inline-formula> can be achieved by changing the global reference phase of the 0/1 coding arrangement in the spatially fed architecture, while 1-bit phase resolution is used in the element level. As verification, a square patch with four slots loaded with two positive-intrinsic–negative (PIN) diodes is exploited as an RA element with 1-bit phase independent control of dual-LP. Then, the RA aperture contains 16 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times16$ </tex-math></inline-formula> elements, where 512 PIN diodes are integrated to control each state independently by a field-programmable gate array (FPGA), excited by a linearly polarized horn is developed and fabricated. Besides, the superposition of the aperture field approach is used to optimize the CP radiation performance, especially the axial ratio (AR). The measured results of the prototype demonstrate the simultaneous multipolarization reconfigurable and the beam-steering capability, where scanning beams are up to 60° in horizontal and vertical planes. The proposed low-lost design is believed to be a promising candidate for mobile communication and cognitive radar applications.

This paper proposes a new design of dual-band reactively loaded annular slot antenna for dual-sense circular polarization radiation. Two concentric annular slots excited by a common microstrip feedline are employed to realize dual-band operation. Each slot can radiate a circularly polarized (CP) wave with a specified sense at its one or one-and-a-half wavelength resonance, given that an appropriately valued reactive component, i.e., capacitor or inductor, is introduced at a pre-determined location. A small frequency ratio (FR) can be achieved between the two oppositely sensed CP bands when a capacitor and an inductor are loaded, respectively, onto the inner and outer annular slots. Contrarily, two oppositely sensed CP bands that possess a large FR can be yielded when an inductor and a capacitor are loaded onto the inner and outer annular slots, respectively. For experimental verification, two antenna prototypes with FRs of 1.63 and 2.41 have been designed, fabricated, and measured. The measurement results exhibit a good agreement with the simulated ones. Details of design concerns and experimental results are presented and discussed.

Multiple signal classification (MUSIC) has been widely applied in wireless communications for direction-of-arrival (DOA) estimation. For massive multiple-input multiple-output (MIMO) systems operating at millimeter-wave bands, hybrid analog-digital structure has been adopted in transceiver design to reduce the cost of radio frequency chains. In hybrid massive MIMO systems, the received signals at the antennas are not sent to the receiver directly, and spatial covariance matrix, which is essential in MUSIC algorithm, is thus unavailable. As a consequence, MUSIC algorithm cannot be directly used in hybrid massive MIMO systems. In this letter, we propose a beam sweeping approach for spatial covariance matrix reconstruction in hybrid massive MIMO systems. In particular, analog beamformer switches the beam direction to a group of predetermined DOA angles in turn, and then the spatial covariance matrix can be reconstructed by solving a set of linear equations. Insightful analysis on the reconstruction accuracy is also presented in this letter. Simulation results show that the proposed approach can reconstruct the spatial covariance matrix accurately so that MUSIC algorithm can be well used for DOA estimation in hybrid massive MIMO systems.

With a booming number of wireless Internet-of-Things devices, satellite communications have been recognized as a key pillar to support massive communication and ubiquitous connectivity in sixth-generation usage scenarios. In the meanwhile, such expansion of space-terrestrial integrated networks makes satellite radio spectrum management complicated. To facilitate spectrum surveillance and efficiently utilize spectrum resources, space-based electromagnetic spectrum monitoring becomes an urgent demand. This paper first investigates state-of-the-art ground-based spectrum monitoring schemes and satellite spectrum monitoring schemes. As crucial enabling technologies for satellite spectrum monitoring, satellite spectrum sensing and database technologies are systematically outlined, as well as their characteristics and limitations. To tackle with the limitations, this paper proposes a space-based spectrum situational awareness method with spectrum situational maps. By applying generative adversarial networks, the spatial correlation of satellite spectrum data is intrinsically utilized to visualize the distribution of radio spectrum situational information in spatial domain. In addition, challenges in monitoring uplink transmissions with narrow directional beams, as in low-Earth orbit satellite internet, are discussed. To handle this issue, a novel satellite spectrum monitoring scheme is proposed by using reinforcement learning and target probability map. The scheme is also validated by numerical results with a case study.

A 2-stage acceleration theory for luminous flux depreciation testing at LED lamp/luminaire level is developed to reduce the test time from 6,000 hours to less than 2,000 hours. Such an acceleration theory is based on the exponential decay model and Arrhenius acceleration equation. Three key parameters, namely, activation energy, operating junction temperature, and accelerated testing junction temperature are obtained from massive proven LM80 data sets, nominal junction design temperature, and maximum allowed ambient temperature in operating conditions. A “master curve” that describes the minimum requirement of the luminous decay is defined, and the curve is associated with a certain design junction temperature. Such a design junction temperature matches the maximum junction temperature where LM80 data are enveloped in the master curve. The corresponding acceleration test procedures have been established by considering the currently available measurement capabilities. Considerable amount of representative lamp/luminaire samples, which directly came from market, have been tested to validate the theory. The results show that the proposed accelerated lifetime test is equivalent to the current 6000h test. In addition, the newly developed accelerated test can eliminate those products with either poor LED sources, or poor system thermal design, or poor electronics system (including driver system) that cannot sustain sufficient temperature storage period.

Appropriate candidate frequency bands are extremely important for the development of future 5G systems. In this work, the researches on 5G spectrum around the world are summarized. Then the potential candidate frequency bands for 5G systems are investigated based on practical utilization of spectrum in China. For spectrum below 6GHz, the feasibility of possible frequency bands for 5G system are analyzed, which mainly come from 2G/3G/4G spectrum re-farming, the spectrum identified by footnotes for IMT systems in Regulations on the Radio Frequency Allocation of China, and potential candidate bands from WRC-15 Agenda Item 1.1. Moreover, propagation characteristics of WRC-15 candidate frequency bands proposed by China are measured and modeled to verify their effectiveness. For spectrum above 6GHz, the potential candidate frequency bands for 5G systems are selected based on the preliminary analysis of spectrum allocation, allotment and the current usage in China. Suggestions are provided for further studies on 5G spectrum.