Personal Characteristics as determinants of Entrepreneurial Self-Efficacy among University Students in Pakistan

Entrepreneurship is considered as a solution to unemployment. It is believed that Entrepreneurial Self-Efficacy (ESE) is imperative for a person to be an entrepreneur. This study aims to examine the determinants of ESE among university students in Pakistan. This is one of the fundamental constructs in the psychology of entrepreneurship research and often integrated in entrepreneurial intentions models to explain why some persons are more likely than others to become entrepreneurs. Entrepreneurial Self-Efficacy Scale prepared by Chen, Greene, and Crick (1998) was used in this study for collecting data. Total 800 questionnaires were distributed among conveniently selected students out of which 742 completely filled questionnaires were returned with a response rate of 92.75%. The results revealed a significant difference between bachelor and master class students in terms of ESE. The model R-squared indicated that 5.7 percent of the variation in the ESE is explained by the personal characteristics. The paper concludes by pointing out some limitations of the study and discussing the possible effect of personal characteristics on ESE

Expanding cellular coverage via cell-edge deployment in heterogeneous networks: spectral efficiency and backhaul power consumption perspectives

Heterogeneous small-cell networks (HetNets) are considered to be a standard part of future mobile networks where operator/consumer deployed small-cells, such as femtocells, relays, and distributed antennas (DAs), complement the existing macrocell infrastructure. This article proposes the need-oriented deployment of smallcells and device-to-device (D2D) communication around the edge of the macrocell such that the small-cell base stations (SBSs) and D2D communication serve the cell-edge mobile users, thereby expanding the network coverage and capacity. In this context, we present competitive network configurations, namely, femto-on-edge, DA-onedge, relay-on-edge, and D2D-communication on- edge, where femto base stations, DA elements, relay base stations, and D2D communication, respectively, are deployed around the edge of the macrocell. The proposed deployments ensure performance gains in the network in terms of spectral efficiency and power consumption by facilitating the cell-edge mobile users with small-cells and D2D communication. In order to calibrate the impact of power consumption on system performance and network topology, this article discusses the detailed breakdown of the end-to-end power consumption, which includes backhaul, access, and aggregation network power consumptions. Several comparative simulation results quantify the improvements in spectral efficiency and power consumption of the D2D-communication-onedge configuration to establish a greener network over the other competitive configurations

A Novel Airborne Self-organising Architecture for 5G+ Networks

Network Flying Platforms (NFPs) such as unmanned aerial vehicles, unmanned balloons or drones flying at low/medium/high altitude can be employed to enhance network coverage and capacity by deploying a swarm of flying platforms that implement novel radio resource management techniques. In this paper, we propose a novel layered architecture where NFPs, of various types and flying at low/medium/high layers in a swarm of flying platforms, are considered as an integrated part of the future cellular networks to inject additional capacity and expand the coverage for exceptional scenarios (sports events, concerts, etc.) and hard-to-reach areas (rural or sparsely populated areas). Successful roll-out of the proposed architecture depends on several factors including, but are not limited to: network optimisation for NFP placement and association, safety operations of NFP for network/equipment security, and reliability for NFP transport and control/signaling mechanisms. In this work, we formulate the optimum placement of NFP at a Lower Layer (LL) by exploiting the airborne Self-organising Network (SON) features. Our initial simulations show the NFP-LL can serve more User Equipment (UE)s using this placement technique.Comment: 5 pages, 2 figures, conference paper in IEEE VTC-Fall 2017, in Proceedings IEEE Vehicular Technology Conference (VTC-Fall 2017), Toronto, Canada, Sep. 201

Spatial and Social Paradigms for Interference and Coverage Analysis in Underlay D2D Network

The homogeneous Poisson point process (PPP) is widely used to model spatial distribution of base stations and mobile terminals. The same process can be used to model underlay device-to-device (D2D) network, however, neglecting homophilic relation for D2D pairing presents underestimated system insights. In this paper, we model both spatial and social distributions of interfering D2D nodes as proximity based independently marked homogeneous Poisson point process. The proximity considers physical distance between D2D nodes whereas social relationship is modeled as Zipf based marks. We apply these two paradigms to analyze the effect of interference on coverage probability of distance-proportional power-controlled cellular user. Effectively, we apply two type of functional mappings (physical distance, social marks) to Laplace functional of PPP. The resulting coverage probability has no closed-form expression, however for a subset of social marks, the mark summation converges to digamma and polygamma functions. This subset constitutes the upper and lower bounds on coverage probability. We present numerical evaluation of these bounds on coverage probability by varying number of different parameters. The results show that by imparting simple power control on cellular user, ultra-dense underlay D2D network can be realized without compromising the coverage probability of cellular user.Comment: 10 pages, 10 figure

The outbreak of rhinoceros beetle (Oryctes rhinoceros) in oil palm at selected oil palm plantations / Muhammad Shakir Zakaria

Oryctes rhinoceros also known as rhinoceros beetle and the most important pest cause huge damage on selected oil palm crop in plantation area. This study aims to generate useful information about the population rhinoceros beetle and their ecology in order to help farmers in reducing of population and huge losses on the oil palm crop that caused by rhinoceros beetle in their field. The objectives of the study were to determine the abundance of rhinoceros beetle over a year in replanting, immature and mature at selected oil palm plantations and evaluate the related factors that affect the population of rhinoceros beetle. Thus study started from 5th August 2017 until 30th October 2017 and was carried out in Parit Jawa, Batu Pahat and Tangkak, Johor and required 11 samples of pheromone traps. As a result, comparison between graph showed that Tangkak area have greater amount of beetle compared to another area. However, there was no significant differece between population of rhinoceros beetle in immature and mature (P-value=0.671>0.05). In addition, the result for the mature and replanting (P-value=0.071>0.05) still showed there was no significant difference. Moreover, the comparisons number of rhinoceros beetle between in immature and mature oil palms showed there was significant different (P<0.05). While, the lowest number of beetle population is at immature area or Batu Pahat, Johor. All the result show that all beetle population is fluctuate but still not achieve threshold level. The results indicate that replanting site can cause high population of beetle and need take care more seriously to avoid the production of oil palm became lowered

How to Solve the Fronthaul Traffic Congestion Problem in H-CRAN?

The design of efficient wireless fronthaul connections for future heterogeneous networks incorporating emerging paradigms such as heterogeneous cloud radio access network (H-CRAN) has become a challenging task that requires the most effective utilization of fronthaul network resources. In this paper, we propose and analyze possible solutions to facilitate the fronthaul traffic congestion in the scenario of Coordinated Multi-Point (CoMP) for 5G cellular traffic which is expected to reach ZetaByte by 2017. In particular, we propose to use distributed compression to reduce the fronthaul traffic for H-CRAN. Unlike the conventional approach where each coordinating point quantizes and forwards its own observation to the processing centre, these observations are compressed before forwarding. At the processing centre, the decompression of the observations and the decoding of the user messages are conducted in a joint manner. Our results reveal that, in both dense and ultra-dense urban small cell deployment scenarios, the usage of distributed compression can efficiently reduce the required fronthaul rate by more than 50% via joint operation

Collaborative Spectrum Sensing Based on Upper Bound on Joint PDF of Exreme Eigenvalues

Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes often depend on asymptotic assumptions since the distribution of ratio of extreme eigenvalues is exceptionally mathematically complex to compute in practice. In this paper, a new approach to determine the distribution of ratio of the largest and the smallest eigenvalues is introduced to calculate the decision threshold and sense the spectrum. In this context, we derive a simple and analytically tractable expression for the distribution of the ratio of the largest and the smallest eigenvalues based on upper bound on the joint probability density function (PDF) of the largest and the smallest eigenvalues of the received covariance matrix. The performance analysis of proposed approach is compared with the empirical results. The decision threshold as a function of a given probability of false alarm is calculated to illustrate the effectiveness of the proposed approach

Eigenvalue Ratio Detection Based on Exact Moments of Smallest and Largest Eigenvalues

Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes always depend on asymptotic assumptions since the close-formed expression of exact eigenvalues ratio distribution is exceptionally complex to compute in practice. In this paper, non-asymptotic spectrum sensing approach to approximate the extreme eigenvalues is introduced. In this context, the Gaussian approximation approach based on exact analytical moments of extreme eigenvalues is presented. In this approach, the extreme eigenvalues are considered as dependent Gaussian random variables such that the joint probability density function (PDF) is approximated by bivariate Gaussian distribution function for any number of cooperating secondary users and received samples. In this context, the definition of Copula is cited to analyze the extent of the dependency between the extreme eigenvalues. Later, the decision threshold based on the ratio of dependent Gaussian extreme eigenvalues is derived. The performance analysis of our newly proposed approach is compared with the already published asymptotic Tracy-Widom approximation approach

Backhaul-aware Robust 3D Drone Placement in 5G+ Wireless Networks

Using drones as flying base stations is a promising approach to enhance the network coverage and area capacity by moving supply towards demand when required. However deployment of such base stations can face some restrictions that need to be considered. One of the limitations in drone base stations (drone-BSs) deployment is the availability of reliable wireless backhaul link. This paper investigates how different types of wireless backhaul offering various data rates would affect the number of served users. Two approaches, namely, network-centric and user-centric, are introduced and the optimal 3D backhaul-aware placement of a drone-BS is found for each approach. To this end, the total number of served users and sum-rates are maximized in the network-centric and user-centric frameworks, respectively. Moreover, as it is preferred to decrease drone-BS movements to save more on battery and increase flight time and to reduce the channel variations, the robustness of the network is examined as how sensitive it is with respect to the users displacements.Comment: in Proc. IEEE ICC2017 Workshops, FlexNets201