Renal Denervation (RDN) has been developed as a potential treatment for hypertension that is resistant to traditional antihypertensive medication. This technique involves the ablation of nerve fibers around the renal artery from inside the blood vessel, which is intended to suppress sympathetic nerve activity and result in an antihypertensive effect. Currently, clinical investigation is underway to evaluate the effectiveness of RDN in treating treatment-resistant hypertension. Although radio frequency (RF) ablation catheters are commonly used, their heating capacity is limited. Microwave catheters are being considered as another option for RDN. We aim to solve the technical challenges of applying microwave catheters to RDN. In this paper, we designed a catheter with a helix structure and a microwave (2.45 GHz) antenna. The antenna is a coaxial slot antenna, the dimensions of which were determined by optimizing the reflection coefficient through simulation. The measured catheter reflection coefficient is -23.6 dB using egg white and -32 dB in the renal artery. The prototype catheter was evaluated by in vitro experiments to validate the simulation. The procedure performed successfully with in vivo experiments involving the ablation of porcine renal arteries. The pathological evaluation confirmed that a large area of the perivascular tissue was ablated (> 5 mm) in a single quadrant without significant damage to the renal artery. Our proposed device allows for control of the ablation position and produces deep nerve ablation without overheating the intima or surrounding blood, suggesting a highly capable new denervation catheter.

Japan encounters an urgent issue of “Carbon Neutrality” as a member of the international world and is required to make the action plans to accomplish this issue, i.e., the zero emission of CO2 by 2050. Our world must change the industries to adapt to the electrification based on the renewable powers. Microwave chemistry is a candidate of electrification of industries for the carbon neutrality on the conditions of usage of renewable energy power generation. This invited paper shows an example of “Microwave Pidgeon process” for smelting magnesium in which heating with burning fossil coals can be replaced with microwave energy for discussing how microwave technology should be developed for that purpose from both the academic and industrial sides.

Considering the non-convexity of hybrid precoding and the hardware constraints of practical systems, a hybrid precoding architecture, which combines limited-resolution overlapped phase shifter networks with lens array, is investigated. The analogy part is a beam selection network composed of overlapped low-resolution phase shifter networks. In particular, in the proposed hybrid precoding algorithm, the analog precoding improves array gain by utilizing the quantization beam alignment method, whereas the digital precoding schemes multiplexing gain by adopting a Wiener Filter precoding scheme with a minimum mean square error criterion. Finally, in the sparse scattering millimeter-wave channel for the uniform linear array, the proposed method is compared with the existing scheme by computer simulation by using the ideal channel state information and the non-ideal channel state information. It is concluded that the proposed scheme performs better in low signal-to-noise regions and can achieve a good compromise between system performance and hardware complexity.

Extremely low-voltage charge pump (ELV-CP) and its dedicated multi-stage driver (MS-DRV) for sub-60-mV thermoelectric energy harvesting are proposed. The proposed MS-DRV utilizes the output voltages of each ELV-CP to efficiently boost the control clock signals. The boosted clock signals are used as switching signals for each ELV-CP and MS-DRV to turn switch transistors on and off. Moreover, reset transistors are added to the MS-DRV to ensure an adequate non-overlapping period between switching signals. Measurement results demonstrated that the proposed MS-DRV can generate boosted clock signals of 350 mV from input voltage of 60 mV. The ELV-CP can boost the input voltage of 100 mV with 10.7% peak efficiency. The proposed ELV-CP and MS-DRV can boost the low input voltage of 56 mV.

Reliability is an important figure of merit of the system and it must be satisfied in safety-critical applications. This paper considers parallel applications on heterogeneous embedded systems and proposes a two-phase algorithm framework to minimize energy consumption for satisfying applications’ reliability requirement. The first phase is for initial assignment and the second phase is for either satisfying the reliability requirement or improving energy efficiency. Specifically, when the application’s reliability requirement cannot be achieved via the initial assignment, an algorithm for enhancing the reliability of tasks is designed to satisfy the application’s reliability requirement. Considering that the reliability of initial assignment may exceed the application’s reliability requirement, an algorithm for reducing the execution frequency of tasks is designed to improve energy efficiency. The proposed algorithms are compared with existing algorithms by using real parallel applications. Experimental results demonstrate that the proposed algorithms consume less energy while satisfying the application’s reliability requirements.

Radiation-induced temporal errors become a significant issue for circuit reliability. We measured the pulse widths of radiation-induced single event transients (SETs) from pMOSFETs and nMOSFETs separately. Test results show that heavy-ion induced SET rates of nMOSFETs were twice as high as those of pMOSFETs and that neutron-induced SETs occurred only in nMOSFETs. It was confirmed that the SET distribution from inverter chains can be estimated using the SET distribution from pMOSFETs and nMOSFETs by considering the difference in load capacitance of the measurement circuits.

In this paper, we consider an orthogonal frequency division multiple access (OFDMA)-based multiuser full-duplex wireless powered communication network (FD WPCN) system with beamforming (BF) at an energy transmitter (ET). The ET performs BF to efficiently transmit energy to multiple users while suppressing interference to an information receiver (IR). Multiple users operating in full-duplex mode harvest energy from the signals sent by the ET while simultaneously transmitting information to the IR using the harvested energy. We analytically demonstrate that the FD WPCN is superior to its half-duplex (HD) WPCN counterpart in the high-SNR regime. We propose a transmitter design method that maximizes the sum rate by determining the BF at the ET, power allocation at both the ET and users, and sub-band allocation. Simulation results show the effectiveness of the proposed method.

Aiming at the problem of “energy hole” caused by random distribution of nodes in large-scale wireless sensor networks (WSNs), this paper proposes an adaptive energy-efficient balanced uneven clustering routing protocol (AEBUC) for WSNs. The competition radius is adaptively adjusted based on the node density and the distance from candidate cluster head (CH) to base station (BS) to achieve scale-controlled adaptive optimal clustering; in candidate CHs, the energy relative density and candidate CH relative density are comprehensively considered to achieve dynamic CH selection. In the inter-cluster communication, based on the principle of energy balance, the relay communication cost function is established and combined with the minimum spanning tree method to realize the optimized inter-cluster multi-hop routing, forming an efficient communication routing tree. The experimental results show that the protocol effectively saves network energy, significantly extends network lifetime, and better solves the “energy hole” problem.

The fifth-generation (5G) new radio (NR) standard employs ultra-reliable and low-latency communication (URLLC) to provide real-time wireless interactive capability for the internet of things (IoT) applications. To satisfy the stringent latency and reliability demands of URLLC services, grant-free (GF) transmissions with the K-repetition transmission (K-Rep) have been introduced. However, fading fluctuations can negatively impact signal quality at the base station (BS), leading to an increase in the number of repetitions and raising concerns about interference and energy consumption for IoT user equipment (UE). To overcome these challenges, this paper proposes novel adaptive K-Rep control schemes that employ site diversity reception to enhance signal quality and reduce energy consumption. The performance evaluation demonstrates that the proposed adaptive K-Rep control schemes significantly improve communication reliability and reduce transmission energy consumption compared with the conventional K-Rep scheme, and then satisfy the URLLC requirements while reducing energy consumption.

In this paper, we investigate a wireless-powered relays assisted batteryless IoT network based on the non-linear energy harvesting model, where there exists an energy service provider constituted by the hybrid access point (HAP) and an IoT service provider constituted by multiple clusters. The HAP provides energy signals to the batteryless devices for information backscattering and the wireless-powered relays for energy harvesting. The relays are deployed to assist the batteryless devices with the information transmission to the HAP by using the harvested energy. To model the energy interactions between the energy service provider and IoT service provider, we propose a Stackelberg game based framework. We aim to maximize the respective utility values of the two providers. Since the utility maximization problem of the IoT service provider is non-convex, we employ the fractional programming theory and propose a block coordinate descent (BCD) based algorithm with successive convex approximation (SCA) and semi-definite relaxation (SDR) techniques to solve it. Numerical simulation results confirm that compared to the benchmark schemes, our proposed scheme can achieve larger utility values for both the energy service provider and IoT service provider.

This paper summarizes recent reports on the internet's energy consumption and the internet's benefits on climate actions. It discusses energy-efficiency and the need for a common standard for evaluating the climate impact of future communication technologies and suggests a model that can be adapted to different internet applications such as streaming, online reading and downloading. The two main approaches today are based on how much data is transmitted or how much time the data is under way. The paper concludes that there is a need for a standardized method to estimate energy consumption and CO2 emission related to internet services. This standard should include a method for energy-optimizing future networks, where every Wh will be scrutinized.

In the current heterogeneous wireless communication system, the sharp rise in energy consumption and the emergence of new service types pose great challenges to nowadays radio access network selection algorithms which do not take care of these new trends. So the proposed energy efficiency based multi-service heterogeneous access network selection algorithm-ESRS (Energy Saving Radio access network Selection) is intended to reduce the energy consumption caused by the traffic in the mobile network system composed of Base Stations (BSs) and Access Points (APs). This algorithm models the access network selection problem as a Multiple-Attribute Decision-Making (MADM) problem. To solve this problem, lots of methods are combined, including analytic Hierarchy Process (AHP), weighted grey relational analysis (GRA), entropy theory, simple additive weight (SAW), and utility function theory. There are two main steps in this algorithm. At first, the proposed algorithm gets the result of the user QoS of each network by dealing with the related QoS parameters, in which entropy theory and AHP are used to determine the QoS comprehensive weight, and the SAW is used to get each network's QoS. In addition to user QoS, parameters including user throughput, energy consumption utility and cost utility are also calculated in this step. In the second step, the fuzzy theory is used to define the weight of decision attributes, and weighted grey relational analysis (GRA) is used to calculate the network score, which determines the final choice. Because the fuzzy weight has a preference for the low energy consumption, the energy consumption of the traffic will be saved by choosing the network with the least energy consumption as much as possible. The simulation parts compared the performance of ESRS, ABE and MSNS algorithms. The numerical results show that ESRS algorithm can select the appropriate network based on the service demands and network parameters. Besides, it can effectively reduce the system energy consumption and overall cost while still maintaining a high overall QoS value and a high system throughput, when compared with the other two algorithms.

Energy harvesting has been widely investigated as a potential solution to supply power for Internet of Things (IoT) devices. Computing devices must operate intermittently rather than continuously, because harvested energy is unstable and some of IoT applications can be periodic. Therefore, processors for IoT devices with intermittent operation must feature a hibernation mode with zero-standby-power in addition to energy-efficient normal mode. In this paper, we describe the layout design and measurement results of a nonvolatile standard cell memory (NV-SCM) and nonvolatile flip-flops (NV-FF) with a nonvolatile memory using Fishbone-in-Cage Capacitor (FiCC) suitable for IoT processors with intermittent operations. They can be fabricated in any conventional CMOS process without any additional mask. NV-SCM and NV-FF are fabricated in a 180nm CMOS process technology. The area overhead by nonvolatility of a bit cell are 74% in NV-SCM and 29% in NV-FF, respectively. We confirmed full functionality of the NV-SCM and NV-FF. The nonvolatile system using proposed NV-SCM and NV-FF can reduce the energy consumption by 24.3% compared to the volatile system when hibernation/normal operation time ratio is 500 as shown in the simulation.

The complexity and scale of Networks-on-Chip (NoCs) are growing as more processing elements and memory devices are implemented on chips. However, under strict power budgets, it is also critical to lower the power consumption of NoCs for the sake of energy efficiency. In this paper, we therefore present three novel input unit designs for on-chip routers attempting to shrink their power consumption while still conserving the network performance. The key idea behind our designs is to organize buffers in the input units with characteristics of the network traffic in mind; as in our observations, only a small portion of the network traffic are long packets (composed of multiple flits), which means, it is fair to implement hybrid, asymmetric and reconfigurable buffers so that they are mainly targeting at short packets (only having a single flit), hence the smaller power consumption and area overhead. Evaluations show that our hybrid, asymmetric and reconfigurable input unit designs can achieve an average reduction of energy consumption per flit by 45%, 52.3% and 56.2% under 93.6% (for hybrid designs) and 66.3% (for asymmetric and reconfigurable designs) of the original router area, respectively. Meanwhile, we only observe minor degradation in network latency (ranging from 18.4% to 1.5%, on average) with our proposals.

Triboelectric generators have been attracting much attention as electrical power sources in scientific communities and industries. Based on dielectric physics, two microscopic routes are available as current sources: One is charge displacement and the other is dipolar rotation. We have been investigating these routes as power sources for triboelectric generation. In other words, dipolar energy transfer process during a course of depolarization has the potentiality to be utilized as triboelectric generator. In this paper, we show that polyimide polymer film with permanent dipoles, i.e., PMDA-ODA polyimide, can provide current source capacity enhanced at elevated temperature, which is in good agreement with our idea based on dipolar energy mode of triboelectric generator. That is, permanent dipoles rotate quickly at elevated temperature, and act as an enhanced current source in the dipolar energy source model of triboelectric generator.

The supercomputer, “Fugaku”, which ranked number one in multiple supercomputing lists, including the Top500 in June 2020, has various power control features, such as (1) an eco mode that utilizes only one of two floating-point pipelines while decreasing the power supply to the chip; (2) a boost mode that increases clock frequency; and (3) a core retention feature that turns unused cores to the low-power state. By orchestrating these power-performance features while considering the characteristics of running applications, we can potentially gain even better system-level energy efficiency. In this paper, we report on the performance and power consumption of Fugaku using SPEC HPC benchmarks. Consequently, we confirmed that it is possible to reduce the energy by about 17% while improving the performance by about 2% from the normal mode by combining boost mode and eco mode.

Energy management in buildings is vital for reducing electricity costs and maximizing the comfort of occupants. Excess solar generation can be used by combining a battery storage system and a heating, ventilation, and air-conditioning (HVAC) system so that occupants feel comfortable. Despite several studies on the scheduling of appliances, batteries, and HVAC, comprehensive and time scalable approaches are required that integrate such predictive information as renewable generation and thermal comfort. In this paper, we propose an thermal-comfort aware online co-scheduling framework that incorporates optimal energy scheduling and a prediction model of PV generation and thermal comfort with the model predictive control (MPC) approach. We introduce a photovoltaic (PV) energy nowcasting and thermal-comfort-estimation model that provides useful information for optimization. The energy management problem is formulated as three coordinated optimization problems that cover fast and slow time-scales by considering predicted information. This approach reduces the time complexity without a significant negative impact on the result's global nature and its quality. Experimental results show that our proposed framework achieves optimal energy management that takes into account the trade-off between electricity expenses and thermal comfort. Our sensitivity analysis indicates that introducing a battery significantly improves the trade-off relationship.

Proof of Work (PoW), which is a consensus algorithm for blockchain, entails a large number of meaningless hash calculations and wastage of electric power and computational resources. In 2021, it is estimated that the PoW of Bitcoin consumes as much electricity as Pakistan's annual power consumption (91TWh). This is a serious problem against sustainable development goals. To solve this problem, this study proposes Meaningful-PoW (mPoW), which involves a meaningful calculation, namely the application of a genetic algorithm (GA) to PoW. Specifically, by using the intermediate values that are periodically generated through GA calculations as an input to the Hashcash used in Bitcoin, it is possible to make this scheme a meaningful calculation (GA optimization problem) while maintaining the properties required for PoW. Furthermore, by applying a device-binding technology, mPoW can be ASIC resistant without the requirement of a large memory. Thus, we show that mPoW can reduce the excessive consumption of both power and computational resources.

This paper refers to the optimal voltage pair, which minimizes the energy consumption of LSI circuits under a target delay constraint, as a Minimum Energy Point (MEP). This paper proposes an approximation-based implementation method for an MEP tracking system over a wide voltage region. This paper focuses on the MEP characteristics that the energy loss is sufficiently small even though the voltage point changes near the MEP. For example, the energy loss is less than 5% even though the estimated MEP differs by a few tens of millivolts in comparison with the actual MEP. Therefore, the complexity for determining the MEP is relaxed by approximating complex operations such as the logarithmic or the exponential functions in the MEP tracking algorithm, which leads to hardware-/software-efficient implementation. When the MEP tracking algorithm is implemented in software, the MEP estimation time is reduced from 1ms to 13µs by the proposed approximation. When implemented in hardware, the proposed method can reduce the area of an MEP estimation circuit to a quarter. Measurement results of a 32-bit RISC-V processor fabricated in a 65-nm SOTB process technology show that the energy loss introduced by the proposed approximation is less than 2% in comparison with the MEP operation. Furthermore, we show that the MEP can be tracked within about 45 microseconds by the proposed MEP tracking system.

The approximate logarithmic multiplier proposed by Mitchell provides an efficient alternative for processing dense multiplication or multiply-accumulate operations in applications such as image processing and real-time robotics. It offers the advantages of small area, high energy efficiency and is suitable for applications that do not necessarily achieve high accuracy. However, its maximum error of 11.1% makes it challenging to deploy in applications requiring relatively high accuracy. This paper proposes a novel operand decomposition method (OD) that decomposes one multiplication into the sum of multiple approximate logarithmic multiplications to widely reduce Mitchell multiplier errors while taking full advantage of its area savings. Based on the proposed OD method, this paper also proposes an accuracy reconfigurable multiply-accumulate (MAC) unit that provides multiple reconfigurable accuracies with high parallelism. Compared to a MAC unit consisting of accurate multipliers, the area is significantly reduced to less than half, improving the hardware parallelism while satisfying the required accuracy for various scenarios. The experimental results show the excellent applicability of our proposed MAC unit in image smoothing and robot localization and mapping application. We have also designed a prototype processor that integrates the minimum functionality of this MAC unit as a vector accelerator and have implemented a software-level accuracy reconfiguration in the form of an instruction set extension. We experimentally confirmed the correct operation of the proposed vector accelerator, which provides the different degrees of accuracy and parallelism at the software level.