FISH: Finite Projective Plane Based Interference Cancellation for Slotted ALOHA

The continuous increase in traffic demand has leaded to a high increase in power consumption and CO2 emission. Green telecommunications are aiming to develop mechanisms that will allow reduction of OPEX and better energy efficiency without compromising end user perceived quality. Low Power Nodes such as micro cells, picocells and Femto cells, thanks to their low cost and easy deployment, are now very attractive to achieve green telecommunications goals. This article discusses the need for co-existence of Low Power nodes underlaid by High Power nodes in an LTE Radio network leading to what is referred to be Heterogonous Networks. This is to cope with capacity increase need and ensure better energy efficiency. After presenting an overview of both Heterogonous networks and Green telecommunication concept, we will survey statement of art in terms of developed mechanisms to optimize power consumption will be overcome. A set of mechanisms related to i/ Interference management and ii/Power management will be discussed.

MAC layer protocols for wireless ad hoc networks typically assume that the network is homogeneous with respect to the transmit power capability of individual nodes in the network. The IEEE 802.11 MAC protocol has been popular for use in ad hoc networks. We investigate the performance of this protocol when it is used in a network with nodes that transmit at various power levels. We show that overall throughput is lower than the throughput of a network in which all nodes transmit at identical power levels. In addition, low power nodes have a disadvantage in accessing the medium due to higher levels of interference from the high power nodes. We consider propagating the control messages generated by a node wishing to initiate communication to distant nodes so that they may forbear transmissions for some time, thereby allowing clear access to the initiating node. We find that the overhead incurred due to the additional message transmissions outweighs the potential gain achieved by propagating these messages. This indicates that the signalling mechanism used in the IEEE 802.11 standard or the variants thereof are not sufficient to alleviate the loss in throughput and the lack of fairness engendered by networks that are heterogeneous with regard to the transmit power capabilities of individual nodes.

We present an automatic skew minimization approach defined for MapReduce programs and present proposed system that implements this approach as a replacement for an existing MapReduce implementation. The proposed system addresses these challenges and works as follows: From intermediate output from map tasks data skew present in records to solve this problem we create two sets of node mainly of high and low computational power nodes and assign the skewed records to the high computational power nodes and remaining to the low computational power nodes to process further reduce task. We implement proposed system as an extension to Hadoop and evaluate its effectiveness using real applications. The results show that proposed system can reduce job runtime in the presence of skew and adds little to no overhead in the absence of skew in heterogeneous environment.

Over the past decade, the telecommunication industry has witnessed excessive growth in the number of mobile users. Market forecasts envision that there will be nearly 8.6 billion mobile devices worldwide by 2017. This tremendous increase in the number of cellular users demands an expansion in the wireless Base Stations (BSs) for improved coverage and capacity. However, this hike in the deployment of base stations will lead to immense energy consumption, because in mobile networks 70–80 % of the power is consumed by BSs. This upsurge in the energy consumption of telecommunication networks implies an increase in CO\(_{2}\) emissions in the environment. In addition, energy bills also represent a major chunk of wireless network operators’ expenditures. These ecological and economical challenges have provoked the curiosity of telecommunication standardization bodies and researchers in an emerging research area termed ‘energy-aware Heterogeneous Networks (HetNets)’. HetNets are a mix of various cell shapes and sizes, including high power macro cells and low power nodes such as micro cells, pico cells and relays. The large macro cells are responsible for the basic coverage of the cell users, and the small cells are effective in providing higher data rates to their nearby users in dense areas with reduced power consumption. The combination of various BSs with different cell sizes and a wide range of power levels can lead to substantial gains in network energy consumption by creating hotspots and enabling dense spatial reuse. It is envisioned that a dense deployment of low power BSs will take place in the near future. HetNets in particular are considered as a promising solution for Fifth Generation (5G) in order to meet the exponentially growing demand for multimedia traffic. The main focus of this chapter is to investigate optimal energy efficient deployment strategies for low power nodes such as relays and small cells in 5G HetNets. In this chapter, a comprehensive overview of remarkable small cell deployment schemes is presented in order to facilitate the debate on technical challenges in deploying HetNets. It goes on to discuss some useful techniques to mitigate the severe interference in 5G dense HetNets. Finally, a novel Long Term Evolution (LTE)-Advanced relay deployment scheme is introduced using graph theory, not only to address some of the identified deficiencies of existing solutions, but also to optimize the energy efficiency of 5G cellular networks.

Energy harvesting aware topology control with power adaptation in wireless sensor networks

In mobile WiMAX, geo-location is possible at the PSS (personal subscriber station) by using the preamble signals broadcasted by all the RAS (Radio Access Station) simultaneously. Using relative arrival times of signals, user location can be obtained by TDoA (Time Difference of Arrival) positioning. However, sufficient number of RAS should be detected to obtain the location in this method. Since mobile WiMAX system employs cellular network structure, the number of RAS that PSS can detect is limited due to low SNR and CCI (co-channel interference) by neighboring RAS. To detect sufficient number of RAS at the PSS, hearability should be enhanced by increasing SNR (signal to noise ratio) and SIR (signal to interference ratio), which can be achieved using long integration and interference cancellation. In multipath environment, however, interference cancellation does not remove the CCI completely. Therefore, multipath mitigation and interference cancellation method should be merged and solved together. In this paper, detection performance after interference cancellation is analyzed using mobile WiMAX geo-location system. Simulation results show that trilateration is possible in most area of the cell coverage after interference cancellation in multipath environment, except at the vicinity of the RAS.

Machine learning inference has become an essential task for embedded edge devices requiring the deployment of costly deep neural network accelerators onto extremely resource-constrained hardware. Although many optimization strategies have been proposed to improve the efficiency of standalone accelerators, the optimization for end-to-end performance of a computing device with heterogeneous cores is still challenging and often overlooked, especially for low power devices. In this paper, we propose a unified reconfigurable architecture, referred as Neural CPU (NCPU), for low-cost embedded systems. The proposed architecture is built on a binary neural network accelerator with the capability to emulate an in-order RISC-V CPU pipeline. The NCPU supports flexible programmability of RISC-V and maintains data locally to avoid costly core-to-core data transfer. A two-core NCPU SoC is designed and fabricated in a 65nm CMOS process. Compared with the conventional heterogeneous architecture, a single NCPU achieves 35% area reduction and 12% energy saving at 0.4V, which is suitable for low power and low-cost embedded edge devices. The NCPU design also features the capability of smooth switching between general-purpose CPU operation and a binary neural network inference to realize full utilization of the cores. The implemented two-core NCPU SoC achieves an end-to-end performance speed-up of 43% or an equivalent 74% energy saving based on use cases of real-time image classification and motion detection.

In this paper a extensive survey of FDSOI based FET Devices is done for low power application. FD-SOI FET has lots of advantages because of the oxide thickness, Buried Oxide (BOX) layers which helps to prevent from leakage power problem, the structure of FDSOI FET help to boost the researchers to focus on Nano-scale devices. Nowadays people interested in portable and low power devices. Scaling in threshold voltage gives better low power results and the threshold voltage of FD-SOI is 0.3642V [35] which is low compare to conventional MOSFET. Subthreshold swing makes an important role in making low power devices for low power devices Subthreshold Swing must be low, In FDSOI the Subthreshold swing value range between 65-80 [49]. They need devices with low cost, low power, and lower thermal resistance. For these kinds of applications, FD-SOI technology is more efficient.

Device-to-device (D2D) communications have recently attracted much attention for the potential capability to improve spectral efficiency (SE) underlaying the existing heterogeneous networks (HetNets). Due to no sophisticated control, D2D-worked user equipments (DUEs) themselves cannot resist eavesdropping or security attacks. It is urgent to maximize the secure capacity for both cellular users and DUEs. This paper formulates the radio resource-allocation problem to maximize the secure capacity of DUEs for D2D communication underlaying HetNets, which consist of high-power nodes (HPNs) and low-power nodes (LPNs). The optimization objective function with transmit bit rate and power constraints, which is nonconvex and hard to directly derive, is first transformed into a matrix form. Then, the equivalent convex form of the optimization problem is derived according to Perron–Frobenius theory. A heuristic iterative algorithm based on the proximal theory is proposed to solve this equivalent convex problem through evaluating the proximal operator of the Lagrange function. Numerical results show that the proposed radio resource-allocation solution significantly improves the secure capacity with a fast convergence speed.

Small cells are low power nodes, which have lower transmit power than the macro eNodeB. They are regarded as one of the important solutions in long term evolution advanced (LTE-A) to deal with the dramatically increased mobile data traffic. Small cells deployments in LTE-A release 12 with 4 small cells in a cluster suffer from stronger inter-cell interference than heterogeneous network (HetNet) in the previous release of LTE-A, where one small cell exists in a cluster. We investigate the joint least squares channel estimation (JLSCE) over demodulation reference signals (DMRS) spreading in time and frequency resources in LTE-A systems. Furthermore, different receiver structures using least square channel estimation (LSCE) and JLSCE are investigated in small cell deployments with the presence of strong inter-cell interference. Our results show the linear minimum mean square error (LMMSE)-interference rejection combining (IRC) with LSCE is the most efficient receiver structure compared to the enhanced (e)LMMSE-IRC with JLSCE, interference cancellation (IC) with eLMMSE-IRC and maximum ratio combining (MRC) receiver structures for signal detection in small cell deployments.

In order to fully exploit the potentials of the heterogeneous cloud radio access networks (H-CRANs), how to associate the user equipments (UEs) with the appropriate low power nodes (LPNs) is a very essential problem. However, when the fronthaul constraint is limited, the UEs are sensitive to delay, and the LPNs are concerned about the traffic balancing, such a problem has not gained enough attention. In this paper, the aforementioned user association problem is investigated and formulated as a bidirectional matching game, where the UEs are seeking to access the most preferred LPN while the LPNs are seeking to accept the most preferred UEs. To find the solution to the proposed game, an iteration algorithm is proposed, and its computational complexity and convergence are proved as well. Simulation results show that our proposed user association scheme is effective and outperforms the existing schemes-in terms of achieved data rates, delay, traffic balancing and overall utility.

This paper considers the power efficiency and transmission range optimization of wireless sensor nodes. A power consumption model is proposed, and the parameters are presented for several commercially available low-power wireless sensor node devices. Then the optimal transmission ranges to achieve the most energy efficiency are obtained for wireless sensor source nodes and relay nodes, respectively. The power saving for multi-hop transmission is investigated by adopting the optimal transmission range. Numerical results are presented to compare the energy efficiency performance under different scenarios. © 2009 IEEE.

Performance of systems for optical detection depends on the choice of the right detector for the right application. Designers of optical systems for ranging applications can choose from a variety of highly sensitive photodetectors, of which the two most prominent ones are linear mode avalanche photodiodes (LM-APDs or APDs) and Geiger-mode APDs or single-photon avalanche diodes (SPADs). Both achieve high responsivity and fast optical response, while maintaining low noise characteristics, which is crucial in low-light applications such as fluorescence lifetime measurements or high intensity measurements, for example, Light Detection and Ranging (LiDAR), in outdoor scenarios. The signal-to-noise ratio (SNR) of detectors is used as an analytical, scenario-dependent tool to simplify detector choice for optical system designers depending on technologically achievable photodiode parameters. In this article, analytical methods are used to obtain a universal SNR comparison of APDs and SPADs for the first time. Different signal and ambient light power levels are evaluated. The low noise characteristic of a typical SPAD leads to high SNR in scenarios with overall low signal power, but high background illumination can saturate the detector. LM-APDs achieve higher SNR in systems with higher signal and noise power but compromise signals with low power because of the noise characteristic of the diode and its readout electronics. Besides pure differentiation of signal levels without time information, ranging performance in LiDAR with time-dependent signals is discussed for a reference distance of 100 m. This evaluation should support LiDAR system designers in choosing a matching photodiode and allows for further discussion regarding future technological development and multi pixel detector designs in a common framework.

In this work, a small footprint, low power, and light weight sensor node for guided wave detection on laminate composite and metallic structures is presented. This device is meant as a basic building block for smart structure passive sensor networks development. It draws power from a two-wires data-over-power (DoP) network communication interface, which is also used for half-duplex data handling at 200kbps. Each node is roughly 20x24mm, consumes less than 40mW, and weights less than 20 grams, making it attractive for aerospace systems where size, power and weight reduction are crucial. Elastic waves generated from impacts and propagating on the structure are recorded by an innovative, patent-pending, dual-element piezoelectric transducer and processed by an embedded low-voltage 8-bit PIC. A 1Mbit SPI serial SRAM is used for data storage while program instruction are stored in the PIC embedded 7 KB ash. A low-voltage, high-speed, half-duplex RS485 transceiver with an internal, programmable termination resistance is used to interface the PIC to the bus through a filtering mesh of passive components. This mesh also connects to a low-dropout voltage regulator, allowing it to draw power from the DoP bus without interfering with data transmission. A separate gateway device has also been developed: it is capable to simultaneously interface and feed the DoP bus by drawing power either from the USB or from an external power supply. A network counting up to 256 nodes can be implemented and interfaced to a PC for real-time impact detection applications.

Low power nodes have been a hot topic in research, standardization, and industry communities, which is typically considered under an umbrella term called heterogeneous networking. In this paper we look at the problem of deploying optimally low power nodes in the context of relay networking, when an operator connects low power nodes (or small cells) via the wireless backhaul that uses the same spectrum and the same wireless access technology. We present an analytical model that can calculate optimal coordinates for low power nodes based on the input parameters, such as preferred number of nodes, their transmission power, parameters of the environment etc. The analytical calculations are complemented by extensive dynamic system level simulations, by means of which we analyze overall system performance for the obtained coordinates. We also show that even relatively marginal deviations from optimal coordinates can lead to worse system performance.