Power Consumption Constraints Research Articles

On the Buffer Energy Aware Adaptive Relaying in Multiple Relay Network

In this paper, we study a buffer-aided collaborative relaying framework for cooperative communication system composed of one source node, multiple half-duplex DF relays with buffers, and one destination node. A two-phase adaptive relaying scheme is proposed, i.e. , the source transmits data and the relay buffers receive data in the first phase, and all relays collaboratively transmit the buffered data to the destination node in the second phase. To achieve higher temporal and spatial diversity gains, time slots are dynamically allocated according to the state information of wireless channel (CSI), each node’s energy consumption (ESI), and each relay’s buffer (BSI). Lyapunov optimization theory is utilized to maximize the average achievable throughput under buffer stability and power consumption constraints, and an online buffer-energy-aware adaptive (BEAA) scheduling scheme is proposed to jointly consider relay selection, power allocation, and time allocation. It is disclosed that the proposed BEAA scheduling scheme is able to achieve a higher average network throughput by adapting the transmissions according to the CSI, ESI, and BSI. Moreover, it is unveiled that there exists inherent tradeoff among the transmission delay, power consumption, and the achievable throughput. Extensive simulations are presented to validate the efficiency of the proposed adaptive collaborative relaying protocol.

Two-Plus-One Cognitive Cooperation Based on Energy Harvesting and Spatial Multiplexing

In this paper, a novel cognitive cooperation model is investigated, in which one multiantenna secondary user (SU) cooperates with two primary users (PUs), reaching a three-party agreement on how to jointly share the authorized spectrum bands, and meanwhile, energy harvesting (EH) and spatial multiplexing (SM) are introduced to make full use of the specious spectrum and energy resources. We call it the EH-SM-enabled two-plus-one cognitive cooperation and focus on the design of the optimal forwarding vector for PUs, optimal beamforming vector for the SU, and optimal power splitting factor for EH, with the objective to maximize SU's achievable transmission rate subject to both minimum transmission rate requirements for two PUs and maximum power consumption constraint for the SU. The formulated problem is nonconvex and difficult to solve directly. For an effective solution, the original rate maximization problem is transformed into the contrapositive power minimization problem, and a low-complexity optimal algorithm is proposed by jointly employing the bisection and golden section methods. Simulation results show that compared with the existing one-plus-one scheme and non-EH-enabled scheme, the proposed scheme greatly improves the SU's achievable transmission rate and, meanwhile, provides more reliable data transmission for PUs.

A Spaceborne Synthetic Aperture Radar Partial Fixed-Point Imaging System Using a Field- Programmable Gate Array-Application-Specific Integrated Circuit Hybrid Heterogeneous Parallel Acceleration Technique.

With the development of satellite load technology and very large scale integrated (VLSI) circuit technology, onboard real-time synthetic aperture radar (SAR) imaging systems have become a solution for allowing rapid response to disasters. A key goal of the onboard SAR imaging system design is to achieve high real-time processing performance with severe size, weight, and power consumption constraints. In this paper, we analyse the computational burden of the commonly used chirp scaling (CS) SAR imaging algorithm. To reduce the system hardware cost, we propose a partial fixed-point processing scheme. The fast Fourier transform (FFT), which is the most computation-sensitive operation in the CS algorithm, is processed with fixed-point, while other operations are processed with single precision floating-point. With the proposed fixed-point processing error propagation model, the fixed-point processing word length is determined. The fidelity and accuracy relative to conventional ground-based software processors is verified by evaluating both the point target imaging quality and the actual scene imaging quality. As a proof of concept, a field- programmable gate array—application-specific integrated circuit (FPGA-ASIC) hybrid heterogeneous parallel accelerating architecture is designed and realized. The customized fixed-point FFT is implemented using the 130 nm complementary metal oxide semiconductor (CMOS) technology as a co-processor of the Xilinx xc6vlx760t FPGA. A single processing board requires 12 s and consumes 21 W to focus a 50-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384.

A 0.6‐V sub‐mW X‐band RFSOI CMOS LNA with novel complementary current‐reused technique

SummaryA fully integrated 0.6 V low‐noise amplifier (LNA) for X‐band receiver application based on 0.18 μm RFSOI CMOS technology is presented in this paper. To achieve low noise and high gain with the constraint of low voltage and low power consumption, a novel modified complementary current‐reused LNA using forward body bias technique is proposed. A diode connected MOSFET forward bias technique is employed to minimize the body leakage and improve the noise performance. A notch filter isolator is constructed to improve the linearity of low voltage. The measured results show that the proposed LNA achieves a power gain of 11.2 dB and a noise figure of 3.8 dB, while consuming a DC current of only 1.6 mA at supply voltage of 0.6 V. Copyright © 2017 John Wiley & Sons, Ltd.

Hierarchical Predictive Load Control in Smart Grids

In this paper, a hierarchical iterative control algorithm is proposed to optimally balance grid load (both voltage drop and current load) while meeting consumers power demand. The proposed control architecture is based on the assumption that a certain proportion of the consumers can predict their consumption profile and adapt their control strategies to fulfill power consumption constraints. It is assumed that a simplified model of the power grid and a prediction based on historical data for the consumption profile of passive consumers are available. Based on the consumers’ consumption profile predictions, the controller proposes constraints for predictively controlled buildings (PCBs) at critical times, so that these consumers can adapt their consumption strategies in advance. The control algorithm also deals with the case of noncompliant consumers. It has low-communication requirements and consumer information is only shared with the hierarchical controller. The method is verified by simulations of an existing power grid with two PCBs. For this purpose, a grid linearization method and a model predictive controller for a building are suggested.

DYNAMIC VOLTAGE AND FREQUENCY SCALING IN FAULT TOLERANT REAL-TIME SYSTEMS

In this paper, we analyze the faults tolerance capability of hard real-time systems under power consumption constraints. In particular, we are focused on real-time systems in which:1) the fault tolerance is achieved through time redundancy, which is used for re-executing tasks affected by transient faults, and 2) the dynamic voltage scaling used to manage power consumption. We propose a heuristic-based algorithm to find processor frequencies at which each real-time task should be executed so that: 1) the power consumption does not exceed the upper power limit; 2) the fault tolerance capability is maximized, and 3) all real-time requirements of individual tasks are met. Evaluations on synthetic task sets show that the proposed algorithm attains target power consumption level with minimum degradation in fault tolerance.

Energy-Efficient Joint Congestion Control and Resource Optimization in Heterogeneous Cloud Radio Access Networks

The heterogeneous cloud radio access network (HCRAN) is a promising paradigm which integrates the advantages of cloud radio access network (C-RAN) and heterogeneous network (HetNet). In this paper, we study the joint congestion control and resource optimization to explore the energy efficiency (EE)-guaranteed tradeoff between throughput utility and delay performance in a downlink slotted H-CRAN. We formulate the considered problem as a stochastic optimization problem, which maximizes the utility of average throughput and maintains the network stability subject to required EE constraint and transmit power consumption constraints by traffic admission control, user association, resource block allocation and power allocation. Leveraging on the Lyapunov optimization technique, the stochastic optimization problem can be transformed and decomposed into three separate subproblems which can be solved concurrently at each slot. The third mixed-integer nonconvex subproblem is efficiently solved utilizing the continuity relaxation of binary variables and the Lagrange dual decomposition method. Theoretical analysis shows that the proposal can quantitatively control the throughput-delay performance tradeoff with required EE performance. Simulation results consolidate the theoretical analysis and demonstrate the advantages of the proposal from the prospective of queue stability and power consumption.

Pareto Optimization of Adaptive Modulation and Coding Set in Nonlinear Fiber-Optic Systems

In recent coherent optical communications, various high-order modulation formats have been used in conjunction with soft-decision forward error correction (FEC) such as capacity-approaching low-density parity-check (LDPC) codes. With a proper selection of modulation order and FEC overhead, we may be able to achieve the highest spectral efficiency (SE) for a given fiber plant configuration. However, it is often not straightforward to select the best pair of modulation format and FEC overhead due to many factors, including fiber nonlinearity, channel spacing, baud rates, communications distance, link budget, and power consumption. In this paper, we introduce a new framework to design adaptive modulation and coding (AMC) sets based on Pareto efficiency in order to optimize multiple objective functions, more specifically, to achieve higher SE, higher nonlinearity tolerance, and lower power consumption at the same time. We compare various modulation formats and variable-rate LDPC codes based on generalized mutual information (GMI) in nonlinear fiber transmissions. In order to account for the penalty of finite-iteration decoding under a constraint of power consumption, we use required GMI as a new metric for AMC design. With our AMC framework, Pareto-efficient pairs of modulation and coding can be identified to achieve both higher SE and higher nonlinearity tolerance constrained on power consumption.

Energy‐efficient pilot and data power allocation in massive multi‐user multiple‐input multiple‐output communication systems

This study aims to improve the energy efficiency of time-division duplexing massive multi-user multiple-input multiple-output communication systems for both uplink and downlink transmissions. By using minimum mean square error channel estimation, two novel pilot–data power allocation schemes are proposed to minimise the total uplink and downlink transmit power under per-user signal-to-interference-plus-noise ratio (SINR) requirement and per-user power consumption constraints. The proposed schemes take into account the maximum-ratio combining and zero-forcing (ZF) detectors in the uplink transmission together with maximum-ratio transmission and ZF precoder in the downlink transmission. In order to simplify the proposed optimisation problems, lower bounds of the average SINR are derived and used in the power allocation algorithms. The key contribution of this study lies in formulating the original energy-efficient power allocation problem and converting such a complicated optimisation problem to a geometric programming problem. Computer simulation validates the tightness of the derived SINR lower bounds and shows that the proposed schemes can save up to 78% of the total power as compared with the equal power allocation among all the mobile users.

A 0.5-V novel complementary current-reused CMOS LNA for 2.4 GHz medical application

A 0.5-V low noise amplifier (LNA) for 2.4GHz medical application based on 0.18μm CMOS process is presented in this paper. To achieve low noise and high gain with the constraint of low voltage and low power consumption, a novel modified complementary current-reused LNA using forward body bias technology is proposed. A diode connected MOSFET forward bias technique is employed to minimize the body leakage and improve the noise performance. A notch filter isolator with harmonic rejection is constructed to improve the linearity of low voltage. The measured results show that the proposed LNA achieves a power gain of 18.7dB and a noise figure of 1.52dB, while the consuming DC current is only 4.2mA at supply voltage of 0.5V.

Improving Multicore Server Performance and Reducing Energy Consumption by Workload Dependent Dynamic Power Management

The technique of using workload dependent dynamic power management (i.e., variable power and speed of processor cores according to the current workload) to improve system performance and to reduce energy consumption is investigated. Typically, the power supply and the core speed are increased when there are more tasks in a server, such that tasks can be processed faster and the average task response time is reduced. On the other hand, the power supply and the core speed are decreased when there are less tasks in a server, such that energy consumption can be reduced without significant performance degradation. A queueing model of multicore server processors with workload dependent dynamic power management is established. Several speed schemes are proposed and it is demonstrated that for the same average power consumption, it is possible to design a multicore server processor with workload dependent dynamic power management, such that its average task response time is shorter than a multicore server processor of constant speed (i.e., without workload dependent dynamic power management). It is shown that given certain application environment and average power consumption, there is an optimal speed scheme that minimizes the average task response time. For two-speed schemes, the problem of optimal design of a two-speed scheme for given power supply and power consumption model is formulated and solved. It is pointed out that power consumption reduction subject to performance constraints can be studied in a similar way as performance improvement (i.e., average task response time reduction) subject to power consumption constraints. To the best of our knowledge, this is the first work on analytical study of workload dependent dynamic power management.

Spatially Regularized Streaming Sensor Selection

Sensor selection has become an active topic aimed at energy saving, information overload prevention, and communication cost planning in sensor networks. In many real applications, often the sensors' observation regions have overlaps and thus the sensor network is inherently redundant. Therefore it is important to select proper sensors to avoid data redundancy. This paper focuses on how to incrementally select a subset of sensors in a streaming scenario to minimize information redundancy, and meanwhile meet the power consumption constraint. We propose to perform sensor selection in a multi-variate interpolation framework, such that the data sampled by the selected sensors can well predict those of the inactive sensors. Importantly, we incorporate sensors' spatial information as two regularizers, which leads to significantly better prediction performance. We also define a statistical variable to store sufficient information for incremental learning, and introduce a forgetting factor to track sensor streams' evolvement. Experiments on both synthetic and real datasets validate the effectiveness of the proposed method. Moreover, our method is over 10 times faster than the state-of-the-art sensor selection algorithm.

Energy-Efficient Joint Congestion Control and Resource Optimization in Heterogeneous Cloud Radio Access Networks

The heterogeneous cloud radio access network (HCRAN) is a promising paradigm which integrates the advantages of cloud radio access network (C-RAN) and heterogeneous network (HetNet). In this paper, we study the joint congestion control and resource optimization to explore the energy efficiency (EE)-guaranteed tradeoff between throughput utility and delay performance in a downlink slotted H-CRAN. We formulate the considered problem as a stochastic optimization problem, which maximizes the utility of average throughput and maintains the network stability subject to required EE constraint and transmit power consumption constraints by traffic admission control, user association, resource block allocation and power allocation. Leveraging on the Lyapunov optimization technique, the stochastic optimization problem can be transformed and decomposed into three separate subproblems which can be solved concurrently at each slot. The third mixed-integer nonconvex subproblem is efficiently solved utilizing the continuity relaxation of binary variables and the Lagrange dual decomposition method. Theoretical analysis shows that the proposal can quantitatively control the throughput-delay performance tradeoff with required EE performance. Simulation results consolidate the theoretical analysis and demonstrate the advantages of the proposal from the prospective of queue stability and power consumption.

Improving Rare Events Detection in WSN through Cluster-Based Power Control Mechanism

Rare events detection is one of the main applications in Wireless Sensor Networks (WSN) and is currently a central concern of a vast literature. Compressed Sensing (CS) theory has been proved to be quite adapted to this objective. Although this is not the first work on applying CS to sparse events detection in WSN, it is the first to highly justify the validity of the targets detection and counting problem formulation. In order to enhance the CS recovery capacity in WSN, this work considers an approach based on a coherence reduction of the sensing matrix premised on the transmitted power control (PC). Simulation results prove that, under the constraint of equal power consumption, the detection and counting performance is improved when the proposed power control scheme is employed compared to the case without PC.

Secure Communications in the Presence of a Buffer-Aided Wireless-Powered Relay With Self-Energy Recycling

We consider a relay-assisted wireless network, where the energy-harvesting buffer-aided relay node is powered by radio-frequency signals from a source node wishing to communicate with its destination. We propose two secure cooperative protocols for a network composed of a source node equipped with a data buffer communicating with its destination in the presence of a buffer-aided relay node and an eavesdropper. Our proposed protocols are designed based on the channel state information and the buffer state information at the source and relay nodes. The burstiness of data at the source node queue (buffer) and the energy recycling process at the relay are taken into account in our analysis. In addition, we take the decoding and signal processing circuit power consumption constraints into consideration. For the limiting case of an infinite-size battery at the relay, we derive a sufficient condition for the energy queue to saturate. Our numerical results demonstrate the throughput gains of our proposed protocols.

Distributed Energy Efficient Cross-layer Optimization for Multihop MIMO Cognitive Radio Networks with Primary User Rate Protection

Due to the unique physical-layer characteristics associated with MIMO and cognitive radio (CR), the network performance is tightly coupled with mechanisms at the physical, link, network, and transport layers. In this paper, we consider an energy-efficient cross-layer optimization problem in multihop MIMO CR networks. The objective is to balance the weighted network utility and weighted power consumption of SU sessions, with a minimum PU transmission rate constraint and SU power consumption constraints. However, this problem is highly challenging due to the nonconvex PU rate constraint. We propose a solution that features linearization-based alternative optimization method and a heuristic primal recovery method. We further develop a distributed algorithm to jointly optimize covariance matrix at each transmitting SU node, bandwidth allocation at each SU link, rate control at each session source and multihop/multi-path routing. Extensive simulation results demonstrate that the performance of the proposed distributed algorithm is close to that of the centralized algorithm, and the proposed framework provides an efficient way to significantly save power consumption, while achieving the network utility very close to that achieved with full power consumption.

One-Selector One-Resistor Cross-Point Array With Threshold Switching Selector

This paper investigates the impact of threshold switching (TS) selector characteristics on the one-selector one-resistor (1S1R) cross-point array performance. TS selector parameter requirements are extracted for 1 Mb array, considering 1S, 1R cell compatibility, read/write margin, and power consumption constraints. The SPICE simulation results show that the threshold voltage ( $V_{\mathrm {\mathbf {th}}}$ ) and the ON-state resistance ( $R_{s}$ ) are important selector parameters. Low $V_{\mathrm {\mathbf {th}}}$ eliminates 1R disturb issue during the read operation, but this comes at the expense of losing full cell nonlinearity (NL) during the write operation. Increase of $V_{\mathrm {\mathbf {th}}}$ and $R_{s}$ improves the full cell NL and alleviate read disturb issue. However, these reduce 1S1R read window and additional voltages are required for both read and write operations. Compared with selector with nonabrupt current-voltage ( $I$ – $V$ ) characteristics, the TS selector is more favorable for the low-voltage operation. Finally, different reported TS selectors are evaluated, and the improvement directions are suggested.

Throughput-Optimal Link-Layer Design in Power Constrained Hybrid OW/RF Systems

The aim of this paper is to develop link layer transmission schemes for hybrid optical wireless (OW)/radio frequency (RF) systems, with constraints on both per-link and total average power consumption at the transmitter. In this context, we adopt a timeslot structure with a queue for storing the data packets for transmission and model the hybrid channel as an erasure channel with parameters varying along the time-slots according to a Markov chain. Then, a stochastic optimization problem is formulated, where intelligent decisions regarding the number of the packets admitted in the queue and the power levels used in every link, are taken by the hybrid transmitter in each slot. The objective of this formulation is to design a control policy that maximizes the transmitter throughput, while satisfying the power constraints as well. A solution is offered by using the Lyapunov optimization framework and an on-line transmission algorithm is developed. The proposed transmission algorithm takes decisions based only on the status of the queue and the statistical parameters of the OW/RF channel in each time-slot, without requiring any knowledge of the underlying Markov chain of the channel process, or the statistics of the packet arrival process. Furthermore, in order to alleviate the requirement for full feedback at the transmitter, i.e., feedback for every successfully received packet, which is critical for the accurate queue update, we extend our analysis and incorporate reduced-feedback coding schemes. The proposed transmission policy in this scenario still meets the throughput objective and satisfies the power consumption constraints, while a tradeoff between transmission delays and feedback requirements is revealed.

Online test method of FPGA solder joint resistance with low power consumption

Solder joint resistance monitoring is important for electronic system prognostics and system health management. It is noted that the typical built-in self-test method of Field Programmable Gate Array (FPGA) solder joint based on charging and discharging of single capacitance has two main shortcomings of large power consumption and unavailability of the monitored pins in FPGA's functional design. In order to overcome these drawbacks, we propose an online measure method of FPGA solder joint resistance with the constraints of limited pin number and low power consumption in this paper. The model of our method is presented in detail, including external test circuit, internal test IP core and parameter determination. The validity of our proposal with low power consumption is upheld by theoretical studies. Furthermore, the corresponding platform of the novel method is built based on a Xilinx Spartan 6 FPGA, and the relative experiments are conducted. Meanwhile, the experiment results show that the method can be used to online measure the resistance of the solder joint of FPGA with lower power consumption than the typical built-in self-test method.

Outage Equivalence of Opportunistic Relaying and Selection Cooperation in Presence of Co-Channel Interference

In this paper, we investigate two different relay selection schemes, opportunistic relaying (OR) and selection cooperation (SC), for decode-and-forward (DF)-based relay networks consisting of a source, multiple relays, and a destination in the presence of multiple co-channel interferers, where each terminal has a single antenna and operates in a half-duplex mode. For the network, we first extend the conventional OR and SC to relay networks with the direct-path and multiple co-channel interferers, and obtain the exact and closed-form outage probability of the OR. Then, we show that the SC is equivalent to the OR in terms of outage performance for relay networks with the direct-path and multiple co-channel interferers. Finally, we show that the SC and OR are outage-optimal under the aggregate power consumption constraint at the relays for relay networks with the direct-path and multiple co-channel interferers.