Analysis of the decoupled uplink downlink technique for varying path loss exponent in multi-tier HetNet

In this paper, the impact of varying path loss exponent (PLE) on user association probability, decoupled uplink coverage probability as well as decoupled uplink average spectral efficiency in downlink uplink decoupled (DUDe) multi-tier heterogeneous networks, is investigated. We investigate the effect of the difference in path loss exponents in both macro and small cell environments over uplink network performance. It is assumed that the mobile user connected to the macro base station experience different path loss exponent as compared to when connected to small base station. It is observed that the difference of path loss exponents in both cases has significant effect on the user association probability, decoupled uplink coverage probability as well as decoupled uplink average spectral efficiency. Moreover, in order to further support key findings and make sound comparison between coupled and DUDe performance in varying PLE environment, generalized analytical expressions for coupled association probabilities, along with coupled uplink coverage probability and coupled uplink average spectral efficiency have been derived. The analytical results evaluated in this paper are compared with the computer simulation and found in good agreement. Our analysis shows that decoupling technique performs suboptimal for cases where the environments around macro and small base stations are different with respect to each other. The work explained in this paper highlights the limitation of applying DUDe technique in realistic conditions where the PLEs of cellular tiers are not exactly equal to one another.

     

Queue length‐based load balancing in data center networks

Traffic load balancing in data centers is an important requirement. Traffic dynamics and possibilities of changes in the topology (e.g., failures and asymmetries) make load balancing a challenging task. Existing end‐host–based schemes either employ the predominantly used ECN or combine it with RTT to get congestion information of paths. Both congestion signals, ECN and RTT, have limitations; ECN only tells whether the queue length is above or below a threshold value but does not inform about the extent of congestion; similarly, RTT in data center networks is on the scale of up to few hundreds of microseconds, and current data center operating systems lack fine‐grained microsecond‐level timers. Therefore, there is a need of a new congestion signal which should give accurate information of congestion along the path. Furthermore, in end‐host–based schemes, detecting asymmetries in the topology is challenging due to the inability to accurately measure RTT on the scale of microseconds. This paper presents QLLB, an end‐host–based, queue length–based load balancing scheme. QLLB employs a new queue length–based congestion signal that gives an exact measure of congestion along the paths. Furthermore, QLLB uses relative‐RTT to detect asymmetries in the topology. QLLB is implemented in ns‐3 and compared with ECMP, CONGA, and Hermes. The results show that QLLB significantly improves performance of short flows over the other schemes and performs within acceptable level, of CONGA and Hermes, for long flows. In addition, QLLB effectively detects asymmetric paths and performs better than Hermes under high loads.     

Correction to: Similar Feed-forward Loop Crosstalk Patterns may Impact Robust Information Transport Across E. coli and S. Cerevisiae Transcriptional Networks

Mobile Networks and Applications - The original version of this article unfortunately contained a mistake in the author group section. Author Preetam Ghosh’s given name was incorrectly...     

Theoretical bounds for the bit error rate for SAC OCDMA balanced detectors with multiple photodiodes

Photonic Network Communications - In this paper, we derive the theoretical lower and upper bounds for bit error rate (BER) for spectral amplitude coding OCDMA balanced detector (BD) employing...     

Apodized chirped fiber Bragg grating for postdispersion compensation in wavelength division multiplexing optical networks

In this paper, a postdispersion compensation unit is proposed leading to a better performance for the optical communication systems. This unit utilizes a chirped fiber Bragg grating (CFBG). For enhanced performance of the CFBG, a proper apodization function is chosen to improve the quality factor (Q‐factor) and the bit error rate (BER) of the system. A 110‐km wavelength division multiplexing (WDM) optical link is investigated. The system performance is evaluated through its Q‐factor, eye diagram, and BER showing best performance when using the Hamming apodization function.     

Fast and Ultraclean Approach for Measuring the Transport Properties of Carbon Nanotubes

In this work, a fast approach for the fabrication of hundreds of ultraclean field‐effect transistors (FETs) is introduced, using single‐walled carbon nanotubes (SWCNTs). The synthesis of the nanomaterial is performed by floating‐catalyst chemical vapor deposition, which is employed to fabricate high‐performance thin‐film transistors. Combined with palladium metal bottom contacts, the transport properties of individual SWCNTs are directly unveiled. The resulting SWCNT‐based FETs exhibit a mean field‐effect mobility, which is 3.3 times higher than that of high‐quality solution‐processed CNTs. This demonstrates that the hereby used SWCNTs are superior to comparable materials in terms of their transport properties. In particular, the on–off current ratios reach over 30 million. Thus, this method enables a fast, detailed, and reliable characterization of intrinsic properties of nanomaterials. The obtained ultraclean SWCNT‐based FETs shed light on further study of contamination‐free SWCNTs on various metal contacts and substrates.     

Human gait recognition using GEI-based local multi-scale feature descriptors

Multimedia Tools and Applications - Human gait recognition is a biometric technique for persons identification based on their walking manner. This paper proposes a novel gait recognition approach...     

Towards energy efficient duty cycling in underwater wireless sensor networks

Multimedia Tools and Applications - Underwater Wireless Sensor Networks devices are usually battery powered and thereby their lifetime is limited. This issue leads to lose data measurements and...     

Robust palm and knuckle ROI extraction in unconstrained environment

Pattern Analysis and Applications - Palm and knuckle prints can be extracted from a hand using a low-cost camera in a contactless manner. This makes the process of palm and knuckle recognition fast...     

A sliding mode control and artificial neural network based MPPT for a direct grid‐connected photovoltaic source

A robust sliding mode controller for a grid‐connected photovoltaic source is proposed in this paper. The objective of the presented control scheme is to force both the output voltage of the photovoltaic PV source and the power factor at the inverter output to follow a certain trajectory reference. The main idea is to apply the robust sliding mode controller directly to the nonlinear state model of the system composed of the PV source and the inverter with its input and output filters. In order to operate the PV system at the maximum power point and to satisfy the environmental factors, such as solar irradiance and temperature, we included a rigorous maximum power point tracker based on an artificial neural network. Simulation results are presented to illustrate the performance of the proposed control scheme. In addition, we show that the grid current satisfies the harmonic limits of the IEEE standard for interconnecting distributed energy sources with electric power systems.