The paper reviews the evolution of the theory related to meridians and zangfu organs during the Warring States, Qin and Han dynasties, so as to reveal the rules and value of its development. By analyzing historical documents, especially Zubi Shiyimai Jiujing (Moxibustion Classics of Eleven Meridians of Legs and Arms), Yinyang Shiyimai Jiujing (Moxibustion Classic on Eleven Yin and Yang Meridians), Laoguanshan bamboo medical slips of Han Dynasty and lacquer figure of meridian points, the evolutionary stages, i.e. the germination, development, and maturity of meridian-zangfu theory, are explored. In the time of the Warring States, Qin and Han dynasties, the meridian-zangfu related theory was developed from the germination to the maturity. In the classics of the early time, Zubi Shiyimai Jiujing and Yinyang Shiyimai Jiujing demonstrated the preliminary relationship between meridians and zangfu organs, focusing on the physiological connection and pathogenesis of three yin meridians of foot and zangfu organs. In the literature of Laoguanshan bamboo medical slips of Han Dynasty and lacquer figure of meridian points, the physiological connection between the yin meridians of hand and foot, and five zang organs, as well as the related diseases were further clarified; additionally, the meridian-zangfu theory had been developed in the field of diagnosis and treatment. In the era of Chapter of Meridians in Lingshu (Miraculous Pivot), there were up to 31 descriptions relevant with the connection of meridian distribution and zangfu physiological functions. It marks the construction of the "circular" flow of meridians and the interior-exterior communication of zang and fu organs; and enriches the knowledge in diseases, diagnosis and treatment with meridians and zangfu organs involved. The review on the evolution of the meridian-zangfu theory is conductive to supplementing and improving the development history of this theory of early time, and further recognizing its development rules and value. The maturity of this theoretical system not only links the meridians with the five zang and six fu organs, but also provides an important theoretical basis for the diagnosis and treatment of traditional Chinese medicine.
New hardware, such as SmartNICs, has been released to offload network applications in data centers. Off-path SmartNICs, a type of multi-core SoC SmartNICs, have attracted the attention of many researchers. Unfortunatelly, they lack the fully exploration of off-path SmartNICs. In this paper, we use a BlueField SmartNIC as an example to conduct a systematical study on the advantages and disadvantages of off-path SmartNICs. We make a detailed performance characterization on an off-path SmartNIC including computing power and network communication overhead, and propose the following advices: 1) Directly utilize the specific accelerators on the SmartNIC to offload applications; 2) Offload latency-insensitive background processing to the SmartNIC to reduce the load on the host; 3) Regard the SmartNIC as a new endpoint in the network to expand the computing power and storage resources of the server host; 4) Avoid directly employing the design method for systems based on on-path SmartNICs. We apply these advices to several use cases and show the performance improvements.
To achieve the more promising passive beamforming gains in the double-intelligent reflecting surface (IRS) assisted system over the conventional single-IRS system, channel estimation is practically indispensable but also a more challenging problem to tackle, due to the presence of not only the single- but also double-reflection links that are intricately coupled. In this paper, we propose a new and efficient channel estimation scheme for the double-IRS assisted uplink multiple-input multiple-output (MIMO) communication system to resolve the cascaded channel state information (CSI) of both its single- and double-reflection links. First, for the single-user case, the higher-dimensional double-reflection channel is efficiently estimated at the multi-antenna base station (BS) with low training overhead by exploiting the fact that its cascaded channel coefficients are scaled versions of those of a lower-dimensional single-reflection channel. Then, the proposed channel estimation scheme is extended to the multi-user case, where given an arbitrary user's cascaded channel estimated as in the single-user case, the other users' cascaded channels are scaled versions of it and thus can be estimated with reduced training overhead. Simulation results verify the effectiveness of the proposed channel estimation scheme as compared to the benchmark scheme.
Radiative wireless power transfer (WPT) is a promising technology to provide cost-effective and real-time power supplies to wireless devices. Although radiative WPT shares many similar characteristics with the extensively studied wireless information transfer or communication, they also differ significantly in terms of design objectives, transmitter/receiver architectures and hardware constraints, and so on. In this paper, we first give an overview on the various WPT technologies, the historical development of the radiative WPT technology and the main challenges in designing contemporary radiative WPT systems. Then, we focus on the state-of-the-art communication and signal processing techniques that can be applied to tackle these challenges. Topics discussed include energy harvester modeling, energy beamforming for WPT, channel acquisition, power region characterization in multi-user WPT, waveform design with linear and non-linear energy receiver model, safety and health issues of WPT, massive multiple-input multiple-output and millimeter wave enabled WPT, wireless charging control, and wireless power and communication systems co-design. We also point out directions that are promising for future research.
Resource allocation is one of the key issues in long term evolution (LTE) systems. In this paper, we propose an adaptive resource allocation scheme with quality of service (QoS) guarantees to maximize system throughput for high-speed mobile LTE systems. In this scheme, considering that channel quality indicator (CQI) might be changed in fast mobile scenarios which can reduce the system throughput, we first propose a novel CQI feedback method to achieve continue high throughput. Then we optimize the resource blocks (RB) allocation procedure under QoS requirements and adopt a more effective modulation and coding scheme (MCS) selection method to improve the system performances. Through extensive simulations, the results show that the proposed resource allocation scheme can achieve higher system throughput and better performance stability compared with some existing schemes in high-speed mobile LTE systems.
Enabling high-rate, low-latency and ultra-reliable wireless communications between unmanned aerial vehicles (UAVs) and their associated ground pilots/users is of paramount importance to realize their large-scale usage in the future. To achieve this goal, cellular-connected UAV, whereby UAVs for various applications are integrated into the cellular network as new aerial users, is a promising technology that has drawn significant attention recently. Compared to the conventional cellular communication with terrestrial users, cellular-connected UAV communication possesses substantially different characteristics that bring in new research challenges as well as opportunities. In this article, we provide an overview of this emerging technology, by firstly discussing its potential benefits, unique communication and spectrum requirements, as well as new design considerations. We then introduce promising technologies to enable the future generation of three-dimensional (3D) heterogeneous wireless networks with coexisting aerial and ground users. Last, we present simulation results to corroborate our discussions and highlight key directions for future research.
This paper studies a new mobile edge computing (MEC) setup where an unmanned aerial vehicle (UAV) is served by cellular ground base stations (GBSs) for computation offloading. The UAV flies between a given pair of initial and final locations, during which it needs to accomplish certain computation tasks by offloading them to some selected GBSs along its trajectory for parallel execution. Under this setup, we aim to minimize the UAV's mission completion time by optimizing its trajectory jointly with the computation offloading scheduling, subject to the maximum speed constraint of the UAV, and the computation capacity constraints at GBSs. The joint UAV trajectory and computation offloading optimization problem is, however, non-convex and thus difficult to be solved optimally. To tackle this problem, we propose an efficient algorithm to obtain a high-quality suboptimal solution. Numerical results show that the proposed design significantly reduces the UAV's mission completion time, as compared to benchmark schemes.
Simultaneous information and power transfer over the wireless channels potentially offers great convenience to mobile users. Yet practical receiver designs impose technical constraints on its hardware realization, as practical circuits for harvesting energy from radio signals are not yet able to decode the carried information directly. To make theoretical progress, we propose a general receiver operation, namely, dynamic power splitting (DPS), which splits the received signal with adjustable power ratio for energy harvesting and information decoding, separately. Three special cases of DPS, namely, time switching (TS), static power splitting (SPS) and on-off power splitting (OPS) are investigated. The TS and SPS schemes can be treated as special cases of OPS. Moreover, we propose two types of practical receiver architectures, namely, separated versus integrated information and energy receivers. The integrated receiver integrates the front-end components of the separated receiver, thus achieving a smaller form factor. The rate-energy tradeoff for the two architectures are characterized by a so-called rate-energy (R-E) region. The optimal transmission strategy is derived to achieve different rate-energy tradeoffs. With receiver circuit power consumption taken into account, it is shown that the OPS scheme is optimal for both receivers. For the ideal case when the receiver circuit does not consume power, the SPS scheme is optimal for both receivers. In addition, we study the performance for the two types of receivers under a realistic system setup that employs practical modulation. Our results provide useful insights to the optimal practical receiver design for simultaneous wireless information and power transfer (SWIPT).
This paper studies the training design problem for multiple-input single-output (MISO) wireless energy transfer (WET) systems in frequency-selective channels, where the frequency-diversity and energy-beamforming gains can be both reaped to maximize the transferred energy by efficiently learning the channel state information (CSI) at the energy transmitter (ET). By exploiting channel reciprocity, a new two-phase channel training scheme is proposed to achieve the diversity and beamforming gains, respectively. In the first phase, pilot signals are sent from the energy receiver (ER) over a selected subset of the available frequency sub-bands, through which the ET determines a certain number of "strongest" sub-bands with largest antenna sum-power gains and sends their indices to the ER. In the second phase, the selected sub-bands are further trained by the ER, so that the ET obtains a refined estimate of the corresponding MISO channels to implement energy beamforming for WET. A training design problem is formulated and optimally solved, which takes into account the channel training overhead by maximizing the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">net</i> harvested energy at the ER, defined as the average harvested energy offset by that consumed in the two-phase training. Moreover, asymptotic analysis is obtained for systems with a large number of antennas or a large number of sub-bands to gain useful insights on the optimal training design. Finally, numerical results are provided to corroborate our analysis and show the effectiveness of the proposed scheme that optimally balances the diversity and beamforming gains in MISO WET systems with limited-energy training.
Wireless energy transfer (WET) via far-field radio signal has emerged as a new solution for powering wireless networks. To overcome the significant path loss in wireless channels, multi-antenna or multiple-input multiple-output (MIMO) techniques have been proposed to enhance the transmission efficiency and distance for WET. However, in order to reap the large energy beamforming gain in WET, acquiring channel state information (CSI) at the energy transmitter (ET) is an essential task. This task is particularly challenging for WET systems, since existing channel training and feedback methods used for communication receivers cannot be implemented at the energy receiver (ER) due to the hardware limitation. To tackle this problem, in this paper we consider a point-to-point MIMO WET system with transmit energy beamforming, and propose a new channel learning method that requires only one feedback bit from the ER to ET per feedback interval. Each feedback bit indicates the increase or decrease of the harvested energy by the ER between the present and previous intervals, which can be measured without changing the existing hardware at the ER. Based on such feedback information, the ET adjusts transmit energy beamforming in different intervals and at the same time obtains an improved estimate of the MIMO channel by applying the analytic center cutting plane method (AC-CPM). By numerical examples, we show the performance of our proposed new channel learning algorithm for MIMO WET systems in terms of convergence speed and energy transfer efficiency, as compared to existing algorithms.
Problem localization is a critical part of providing crucial system management capabilities to modern distributed environments. One key open challenge is for problem localization solutions to scale for systems containing hundreds or even thousands of nodes, whilst still remaining fast enough to respond to rapid environment changes and sufficiently cost-effective to avoid overloading any management or application component. This paper meets the challenge by introducing two scalable frameworks applicable to a wide range of existing problem localization solutions: one based on a summary-driven, narrow-down procedure, the other through decomposing and decentralizing the problem localization process. Both frameworks, at their best, are able to achieve O(logN) problem localization time and O(1) per node communication load. The contrasting natures of both frameworks provide them with complimentary strengths that make them suitable for different scenarios in practice. We demonstrate our approaches in simulation settings and two real-world environments and show promising scalability benefits that can make a difference in system management operations.
The auto-routing of electromechanical products is studied,and a kind of improved A* algorithm is proposed.First,the discrete grid space model was established for auto-routing,in order to reduce the search space.Second,for multiple-tube routing,the shortest channel constraint,the shortest route constraint and the least bending constraint were introduced,and the constraint model was established for multiple-tube routing.Third,according to these two models,the feasible space weight factor,the channel weight factor and the bending evaluation item were introduced in the A* algorithm evaluation function.At last,a experiment show that a reasonable solution can be achieved by using the improved A* algorithm to search routes for multiple-tube routing of electromechanical products.
This paper studies the system throughput limits of the MIMO broadcast channel for wireless downlink transmission. More specifically, the expected throughput for no-delay-constrained (NDC) traffic and the delay-limited throughput for delay-constrained (DC) traffic are characterized and compared. The multiuser-diversity effect on the delay-limited throughput for DC traffic is discussed for the first time. A novel transmission scheme that can simultaneously support both NDC and DC traffics is proposed. Computer simulation shows that the proposed scheme can approach the system throughput limit effectively provided that it is designed for the correct traffic ratio between NDC and DC services.
