Theoretical study of a group IV p–i–n photodetector with a flat and broad response for visible and infrared detection

We report a theoretical study of a broadband Si/graded-SiGe/Ge/Ge_0.9Sn_0.1 p–i–n photodetector with a flat response based on modulating thickness of the layers in the active region. The responsivity of the photodetector is about 0.57 A/W in the range of 700 to 1800 nm. This structure is suitable for silicon-based epitaxial growth. Annealing is technically applied to form the graded-SiGe. The photodetector reaches a cut-off wavelength at ~2300 nm and a low dark-current density under 3 V reverse bias about 0.17 mA/cm² is achieved theoretical at room temperature. This work is of great significance for silicon-based detection and communication, from visible to infrared.     

Performance of joint source–channel decoding with iterative bit combining and detection

A joint source–channel decoding scheme (JSCD) with iterative bit combining (IBC) is proposed, which exploits two types of a priori information. The first one is the a priori bit probabilities obtained from source statistics, and the second is the channel a priori probabilities obtained from saved extrinsic information of previous transmissions. The JSCD-IBC scheme also incorporates iterative detection as both a stopping criteria and mechanism for triggering retransmissions. This adds an implicit adaptivity to the system and prevents excess iterations/retransmissions from being effected. The performance of the JSCD-IBC scheme is evaluated with four different iterative detection schemes and also two different types of variable length codes, Huffman and reversible variable length codes. Simulation results show that a significant performance gain in terms of bit error rate, throughput, and number of iterations can be achieved with the JSCD-IBC scheme as compared to a separate decoding scheme.     

Efficient primal–dual fixed point algorithms with dynamic stepsize for composite convex optimization problems

Multidimensional Systems and Signal Processing - In this paper, we propose a new primal–dual fixed point algorithm with dynamic stepsize ( $$hbox {PDFP}^{2}O_{DS_{n}}$$ ) for solving convex...     

Auction–Stackelberg game framework for access permission in femtocell networks with multiple network operators

With the explosive growth of indoor data traffic in forthcoming fifth generation cellular networks, it is imperative for mobile network operators to improve network coverage and capacity. Femtocells are widely recognized as a promising technology to address these demands. As femtocells are sold or loaned by a mobile network operator (MNO) to its residential or enterprise customers, MNOs usually employ refunding scheme to compensate the femtocell holders (FHs) providing indoor access to other subscribers by configuring the femtocell to operate in open or hybrid access mode. Due to the selfishness nature, competition between network operators as well as femtocell holders makes it challenging for operators to select appropriate FHs for trading access resources. This inspires us to develop an effective refunding framework, with aim to improve overall network resource utilization, through promoting FHs to make reasonable access permission for well-matched macro users. In this paper, we develop a two-stage auction–Stackelberg game (ASGF) framework for access permission in femtocell networks, where MNO and mobile virtual network operator lease access resources from multiple FHs. We first design an auction mechanism to determine the winner femtocell that fulfils the access request of macro users. We next formulate the access permission problem between the winner femtocell and operators as a Stackelberg game, and theoretically prove the existence of unique equilibrium. As a higher system payoff can be gained by improving individual players’ payoff in the game, each player can choose the best response to others’ action by implementing access permission, while avoiding solving a complicated optimization problem. Numerical results validate the effectiveness of our proposed ASGF based refunding framework and the overall network efficiency can be improved significantly.     

Low-cost and flexible printed graphene–PEDOT:PSS gas sensor for ammonia detection

This work presents a simple, low-cost and practical inkjet-printing technique for fabricating an innovative flexible gas sensor made of graphene–poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) composite film with high uniformity over a large area. An electronic ink prepared by graphene dispersion in PEDOT:PSS conducting polymer solution is inkjet-printed on a transparency substrate with prefabricated electrodes and investigated for ammonia (NH₃) detection at room temperature. Transmission electron microscopy, Fourier transform infrared spectroscopy, UV–visible spectrometer and Raman characterizations confirm the presence of few-layer graphene in PEDOT:PSS polymer matrix and the present of π–π interactions between graphene and PEDOT:PSS. The ink-jet printed graphene–PEDOT:PSS gas sensor exhibits high response and high selectivity to NH₃ in a low concentration range of 25–1000 ppm at room temperature. The attained gas-sensing performance may be attributed to the increased specific surface area by graphene and enhanced interactions between the sensing film and NH₃ molecules via π electrons network. The NH₃-sensing mechanisms of the flexible printed gas sensor based on chemisorbed oxygen interactions, direct charge transfers and swelling process are highlighted.     

Neural network-based multiuser detection for SDMA–OFDM system over IEEE 802.11n indoor wireless local area network channel models

Space division multiple access – orthogonal frequency division multiplexing-based wireless communication has the potential to offer high-spectral efficiency, system performance and capacity. This article proposes an efficient blind multiuser detection (MUD) scheme using artificial neural network models such as the radial basis function. The proposed MUD technique is consistently outperforming the existing minimum mean square error and minimum bit error rate (MBER) MUDs with the performance close to the optimal maximum likelihood (ML) detector. Besides that, the computational complexity of the proposed one is comparatively lower than both the MBER and ML detectors. Further, it can also outperform MBER MUD in the overload scenario, where the number of users is more than that of the number of receiving antennas simulation-based study showing BER performance and complexity are carried out to prove the efficiency of the proposed techniques. This analysis is carried through the IEEE 802.11n standard channel models, which are designed for indoor wireless local area network applications of bandwidth up to 100?MHz at frequencies 2 and 5?GHz.     

Challenges and Solutions for Lithium–Sulfur Batteries with Lean Electrolyte

Lithium–sulfur (Li–S) batteries have high theoretical energy density and are regarded as next-generation batteries. However, their practical energy density is much lower than the theoretical value. In previous studies, the increase of the areal capacity of the cathode and the decrease of the negative/positive ratio can be well achieved, yet the energy density shows no corresponding increase. The main reason is the difficulty in decreasing electrolyte dosage because lean electrolyte inevitably causes the deterioration of reaction kinetics and sulfur utilization. Thus, the electrolyte/active material ratio in the reported works is usually higher than 10 µL mg⁻¹, much higher than that in Li-ion batteries (usually lower than ≈0.3 µL mg⁻¹ for cathode). Although many works have focused on this topic, a systematic discussion is still rare. This review systematically discusses the key challenges and solutions for assembling high-performance lean-electrolyte Li–S batteries. First, the key challenges arising from lean-electrolyte conditions are discussed in detail. Then, the approaches and the recent progress to reduce electrolyte usage, including optimization of electrode porosity and ion conduction, the introduction of electrocatalysis, exploration of new active materials, electrolyte regulation, and Li metal protection are reviewed. Finally, future research directions in lean-electrolyte Li–S batteries are proposed.     

Balancing CapEx reduction and network stability with stable routing–virtual topology capacity adjustment (SR–VTCA)

This paper investigates the merits of the SR–VTCA (stable routing–virtual topology capacity adjustment) approach as a mechanism to find a beneficial trade-off between network stability and reduction in capital expenditures (CapEx). These are two main objectives for the entities that own the optical infrastructure, such as network operators (NOs), and those also acting as Internet service providers (ISPs). The SR–VTCA scheme is a novel approach to adapt transparent optical networks to time-varying traffic by adjusting the number of lightpaths between node pairs, while keeping the IP routing unchanged. Lightpath bundling (LB) and anycast (AS) switching are combined in SR–VTCA operation to advertise lightpath additions/removals to the IP layer as mere adjustments (increments or decrements) in the capacity, allowing to keep the IP routing stable, and thus, simplifying control plane operations. On the contrary, a fully-reconfigurable (FR) network design, where IP routing can be also modified, would increase the burden in the control plane, but at a higher CapEx reduction, since the optical infrastructure is used more efficiently. In this work, we investigate the CapEx overprovision introduced by SR–VTCA with respect to a FR scheme. In order to do this, SR–VTCA planning problem is first modeled as a MILP formulation. A heuristic procedure based on traffic domination is then proposed to solve large instances of the problem. Exhaustive experiments are conducted comparing the SR–VTCA solutions obtained by the aforementioned MILP and heuristic proposal with solutions found by other optimization methods presented in the literature to solve the FR planning problem. Finally, the results show that SR–VTCA can achieve similar results to the FR case in terms of CapEx reduction, while a huge number of IP reroutings are saved by maintaining IP stability. Thus, SR–VTCA provides an advantageous balance between CapEx overprovisioning and the control plane overhead associated with IP rerouting.     

Power Allocation with Max–Min and Min–Max Fairness for Cognitive Radio Networks with Imperfect CSI

This paper consider the power allocation strategies in the cognitive radio (CR) system in the presence of channel estimation errors. As the user has different channel condition in CR systems, different amount of power resource is required to meets the QoS request. In order to guarantee the fairness of each CR user, ensure the interference from the primary user and other CR users meet the QoS requirement of the CR user and limit the interference that is caused by CR users on primary user within the range into the level that primary user can tolerate, we proposed some new power allocation schemes. The targets are to minimize the maximum power allocated to CR users, to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all CR users and to minimize the maximum outage probability over all CR users. The first power allocation scheme can be formulated using Geometric Programming (GP). Since GP problem is equivalent to the convex optimization problem, we can obtain the optimal solutions for the first scheme. The latter two power allocation schemes are not GP problems. We propose iterative algorithms to solve them. Simulation results show that proposed schemes can efficiently guarantee the fairness of CR users under the QoS constraint of the primary user and CR users.     

Performance analysis of weather-dependent satellite–terrestrial network with rate adaptation hybrid free-space optical and radio frequency link

Due to the rapid development of satellite laser communication technology, free-space optical (FSO) links present a promising alternative to traditional radio frequency (RF) links. In this paper, taking the influence of weather factors into consideration, we investigate the performance of the hybrid FSO/RF links where the feeder link operates in the FSO band and the user link operates in the hybrid FSO/RF band. Specifically, the FSO feeder link is modeled by the gamma–gamma distribution in the presence of beam wander and pointing error, and the detection method adopts either the intensity modulation with direct intensity (IM/DD) or heterodyne detection. The RF user link is assumed to follow the shadowed Rician model. In addition, in order to improve the transmission rate of the link under the time-varying satellite–terrestrial channel, a rate adaptation scheme is proposed. The performance of the system under study is evaluated in terms of the outage probability, average bit error rate (BER), and average transmission rate. Our results provide some important insights, for example, (1) due to the constraints of the feeder link and weather factors, there is an upper limit on the outage performance and bit error rate of the hybrid link; (2) the adaptive transmission strategy can significantly improve the transmission rate of the link compared with traditional design.     

Bidirectional Catalyst with Robust Lithiophilicity and Sulfiphilicity for Advanced Lithium–Sulfur Battery

The application of lithium–sulfur batteries (LSBs) is immensely impeded by notorious shuttle effect, sluggish redox kinetics, and irregular Li₂S deposition, which result in large polarization and rapid capacity decay. To obtain the LSBs with high energy density and fast reaction kinetics, herein, a heterostructure composed by nitrogen-deficient graphitic carbon nitride (ND-g-C₃N₄) and MgNCN is fabricated via a magnesiothermic denitriding technology. Lithophilic C₃N₄ with abundant nitrogen-deficient acts as a conductive framework, together with the sulfiphilic MgNCN, lithium-polysulfides (LiPSs) can be effectively captured followed by a regulated Li₂S nucleation. Furthermore, the oxidation conversion kinetics can be accelerated as well. As expected, the LSBs with catalytic MgNCN/ND-g-C₃N₄ as the interlayer exhibit remarkable electrochemical performance with a discharge capacity of 650 mAh g⁻¹ at 4 C. Meanwhile, a low capacity decay of 0.008% per cycle can be reached at 1 C after 400 cycles. Even with a high areal sulfur loading of 5.1 mg cm⁻², outstanding capacity retention can be achieved at 0.5 C (64.18%) and 1 C (90.46%). The presented strategy unlocks a new way for the LSBs design with highly efficient catalyst.     

Cascade controller with sliding-mode-voltage and current-mode for monolithic high frequency DC–DC converters

Modern control theories such as fuzzy control, sliding-mode control, optimal control, neural network control have been widely used in discrete-switching DC–DC converters, While they are seldom used in monolithic integration. Under parameter variation, large supply and load disturbance, high slew-rate current transient, high nonlinearity in today and future power management integrated circuits, linear control theories used in traditional monolithic DC–DC converters cannot satisfy required performance, which make it stringent to use modern control theories in monolithic DC–DC converters. This paper proposes cascade controller which consists of PWM based sliding-mode-voltage control and current-mode control for high frequency DC–DC converters. As long as the dynamic responses of the inner current loop are much faster than the outer sliding-mode-voltage loop, inner and outer loops operate in cascade-mode functionally. This work leads to an easy-to-follow design procedure to design control coefficients. To illustrate the feasibility of the scheme, a monolithic 100 MHz boost DC–DC converter using cascade controller with sliding-mode-voltage and current-mode is designed in SMIC 0.18 μm CMOS process. Several simulations are performed to validate the functionalities of the controller.     

Monolithically integrated μ-capillary electrophoresis with organic light sources and tunable a-Si:H multispectral photodiodes for fluorescence detection

The miniaturization of chemical or biochemical analysis systems to micro- or nanoscale dimension allows dramatic acceleration of chemical processes and a high degree of parallelism. In this paper, we present a monolithically integrated application specific lab-on-microchip device (ALM) [1], [2] for on-chip capillary electrophoresis (μ-CE) with an organic light-emitting diode (OLED) as excitation light source and a tunable a-Si:H multispectral photodiode for colorimetric analysis. The purpose of this work is to adapt the spectral response of a tunable multispectral photodiode to individual fluorescence spectra of different dyes.     

Reversible Temperature-Sensitive Liquid–Solid Triboelectrification with Polycaprolactone Material for Wetting Monitoring and Temperature Sensing

Controlling liquid–solid triboelectrification is highly demanded in a wide range of applications, from electrostatic prevention to energy collection and utilization. Except for traditional unidirectional and irreversible ways, smart approaches are required urgently. Here, a novel temperature response liquid–solid triboelectric nanogenerator (TENG) is reported on the basis of a polycaprolactone (PCL) covered fluorinated alumina for tunable triboelectrification. The PCL conformation is regulated by temperature to endow the substrate controllable surface component and interfacial wettability to manipulate the liquid–solid triboelectricity flexibly. As the temperature rises from 20 to 40 °C, the short circuit current and the open-circuit voltage of the PCL-based TENG are reduced by more than 40 times. When the temperature drops to 20 °C, the electrical output can return to its original level again. Moreover, after one month, the electrical signal is still reversible and stable. In addition to water, the electrical output of organic liquid, such as ethylene glycol, also responds well to temperature. This work initially provides a new strategy for achieving the customizable manipulation of liquid–solid triboelectrification by polymer surface reorganization, gives a new idea for in situ monitoring the interfacial wettability changes, and configures the reconstruction of amphiphilic polymer using triboelectricity.     

Dual Mode Strain–Temperature Sensor with High Stimuli Discriminability and Resolution for Smart Wearables

Strain and temperature are important physiological parameters for health monitoring, providing access to the respiration state, movement of joints, and inflammation processes. The challenge for smart wearables is to unambiguously discriminate strain and temperature using a single sensor element assuring a high degree of sensor integration. Here, a dual-mode sensor with two electrodes and tubular mechanically heterogeneous structure enabling simultaneous sensing of strain and temperature without cross-talk is reported. The sensor structure consists of a thermocouple coiled around an elastic strain-to-magnetic induction conversion unit, revealing a giant magnetoelastic effect, and accommodating a magnetic amorphous wire. The thermocouple provides access to temperature and its coil structure allows to measure impedance changes caused by the applied strain. The dual-mode sensor also exhibits interference-free temperature sensing performance with high coefficient of 54.49 µV °C⁻¹, low strain and temperature detection limits of 0.05% and 0.1 °C, respectively. The use of these sensors in smart textiles to monitor continuously breathing, body movement, body temperature, and ambient temperature is demonstrated. The developed multifunctional wearable sensor is needed for applications in early disease prevention, health monitoring, and interactive electronics as well as for smart prosthetics and intelligent soft robotics.     

A Nash–Stackelberg equilibrium model for internet and network service providers in the demand market—a scenario-based approach

This paper evaluates the optimal pricing for two Internet service providers and two network providers; all are competing on price, which is based on quality. To find the optimal prices of service and network providers and to determine optimal scenarios, a two-stage competition is modeled. In the first stage, network providers compete on market prices by setting the quality in four scenarios. At this stage, we found the equilibrium prices in the market. In the second stage, by obtaining market prices, service providers compete on network prices. Finally, the equilibrium solutions are compared with each other by considering the intensity of market competition in price and quality. It is shown that equilibrium never occurs in the case when the smaller service provider has a higher Internet quality than the other (scenario 2) and the more significant service provider offers a higher Internet quality (scenario 4). Besides, when both Internet service providers offer low-quality Internet (scenario 1) and high-quality Internet (scenario 3), the companies make the most profit. By increasing and decreasing the competition in quality, equilibrium would still exist for the first scenario, and the third scenario, respectively. The intensity of market competition in price behaves oppositely as quality.

     

Radio resource management for LTE-A relay-enhanced cells with spatial reuse and max–min fairness

One of the major issues in LTE-Advanced (LTE-A) systems is the poor capacity at the cell edge. This is mainly due to the interference experienced by the users as a result of the aggressive frequency reuse usually implemented. Relaying offers an attractive solution for this problem by offering better links than those with the eNodeB (eNB) for the terminals suffering from high path loss or high interference. However, adding relays complicates the resource allocation problem at the eNB and therefore the need for more efficient schemes arises. This is also aggravated by the reuse of resource blocks (RBs) by the relays to fully exploit the scarce spectrum, which, in turn, leads to intra-cell interference. In this paper, we study the joint power and resource allocation problem in LTE-A relay-enhanced cells that exploit spatial reuse. To guarantee fairness among users, a max–min fair optimization objective is used. This complex problem is solved using coordinate ascent and the difference of two convex functions (DC) programming techniques and the proposed scheme indeed converges to a local-optimum quickly. This is shown to be a satisfactory solution according to the simulation results that indicate an almost sevenfold increase in the 10th percentile capacity when compared to previously proposed solutions.     

Joint QoE-based user association and efficient cell–carrier distribution for enabling fully hybrid spectrum sharing approach in 5G mmWave cellular networks

Densifying the network by adding more minicell towers or relays throughout a hot spot area while extensively reusing the available spectrum is an essential choice to improve QoS. Unfortunately, this approach can be prohibitively costly. One possible solution to reduce the capital and operating expenditure in such overdensified networks is the adoption of the spectrum-sharing approach. However, both approaches would complicate the interference phenomenon either among inter- or intraoperators, which may cause serious performance degradation. In this paper, a fully hybrid spectrum-sharing (FHSS) approach aided by an efficient cell–carrier distribution was proposed with consideration to the interference dilemma. Moreover, an adaptive hybrid QoE-based mmWave user association (mUA) scheme was presented to assign a typical user to the serving mmWave base station (mBS), which offers the highest achievable data rate. The proposed FHSS approach (with the presented QoE-based mUA) was compared with recent works and with both FHSS approach using the conventional max-SINR-based mUA, which assigns a typical user to the tagged mBS carrying the highest signal-to-interference-plus noise ratio and the baseline scenario (licensed spectrum access). In particular, three spectrum access methods (licensed, semipooled, and fully pooled) were integrated in a hybrid manner to engage improved data rates to users. Numerical results show that the joint cell–carrier distribution and FHSS approach with QoE-based mUA outperform both baselines FHSS with the max-SINR mUA scheme and the licensed spectrum access. Furthermore, results demonstrate the effectiveness of the proposed approach in terms of both operators’ independence and fairness.

     

Achieving Max–Min lifetime and fairness with rate allocation for data aggregation in sensor networks

We consider the rate allocation problem for data aggregation in wireless sensor networks with two objectives: (1) maximizing the minimum (Max–Min) lifetime of an aggregation cluster and (2) achieving fairness among all data sources. The two objectives are generally correlated with each other and usually, they cannot be maximized simultaneously. We adopt a lexicographic method to solve this multi-objective programming problem. First, we recursively induce the Max–Min lifetime for the aggregation cluster. Under the given Max–Min lifetime, we then formulate the problem of maximizing fairness as a convex optimization problem, and derive the optimal rate allocation strategy by iterations. We also present low-complexity algorithms that an aggregation cluster can use to determine the Max–Min network lifetime and the fair rate allocation. Our simulation results validate our analytical results and illustrate the effectiveness of the approach.