Sharing Spectrum UE LTE and Air-Traffic Control Radars in 800 MHz Band, Journal of Telecommunications and Information Technology, 2017, nr 2

The need to ensure LTE network coverage in sparsely populated and rural areas of Europe (ITU Region 1) has led to a massive use of 800 MHz band (band 20) with its good characteristics of radio wave propagation in LTE networks. However, the frequency band of 800 MHz called “digital dividend” in Region 1 is used on a primary basis not only by the terrestrial mobile service but also by air-traffic control radars (ATCR) that can lead to the creation of harmful interferences at the receivers’ input of ATCR. Such scenarios of mutual interferences became possible after granting licenses for LTE-800 frequencies to operators in such countries as Azerbaijan, Kazakhstan, Russia and other CIS countries, so this problem should be solved by operators at the deployment of LTE-800 networks in airports and areas close to them. So far, for such scenarios the ITU and CEPT have not formulated criteria for interference protection. The proposed protection criteria for receivers of ATCR from user devices’ interferences of LTE-800 networks were tested by experimental studies and can provide a solution to the electromagnetic compatibility (EMC) problem in a complex electromagnetic environment of modern airports and cross-order coordination of 800 MHz frequency bands in Region 1

Study of the Process of Packet Arrival at a Multiservice Node

The paper considers the main ways of describing the process that characterizes the arrival of packets to a multiservice node of a telecommunications network. The features of the process under consideration are best represented by the cumulative distribution function A(t). It determines the distribution of the interval size between the moments of arrival of neighboring packets to the multiservice node. These intervals are random values. If it is not possible to perform measurements that allow the choosing of the A(t) function, then the distribution law of random variables is selected based on reasonable assumptions. For telephone switching nodes, the Poisson flow hypothesis was used, which is often similar to the symmetric distribution of the number of calls at time interval t. The results of traffic measurements for multiservice switching nodes showed that the studied distribution is inherently asymmetric. This paper mainly considers the possibility of choosing the A(t) function based on the measurement results presented in a form of the histogram a(t), which contains a series of values. This histogram allows us to obtain the desired distribution as a stepwise function by integration of the a(t). Practical interest is associated with the possibility of reducing the number of readings used to assess the A(t) function. The methods used by some authors are based on the application of arbitrarily chosen functions A(t) with so-called heavy tails. The proposed approach is based on real distributions defined at a finite time interval. As a result of this research, a methodology has been developed to accurately describe the process of packet arrival at the input of the multiservice node. The proposed methodology is based on analytical methods. It guarantees error minimization when investigating the probabilistic characteristics of a switching node in a multiservice network

Study of the Process of Packet Arrival at a Multiservice Node

The paper considers the main ways of describing the process that characterizes the arrival of packets to a multiservice node of a telecommunications network. The features of the process under consideration are best represented by the cumulative distribution function A(t). It determines the distribution of the interval size between the moments of arrival of neighboring packets to the multiservice node. These intervals are random values. If it is not possible to perform measurements that allow the choosing of the A(t) function, then the distribution law of random variables is selected based on reasonable assumptions. For telephone switching nodes, the Poisson flow hypothesis was used, which is often similar to the symmetric distribution of the number of calls at time interval t. The results of traffic measurements for multiservice switching nodes showed that the studied distribution is inherently asymmetric. This paper mainly considers the possibility of choosing the A(t) function based on the measurement results presented in a form of the histogram a(t), which contains a series of values. This histogram allows us to obtain the desired distribution as a stepwise function by integration of the a(t). Practical interest is associated with the possibility of reducing the number of readings used to assess the A(t) function. The methods used by some authors are based on the application of arbitrarily chosen functions A(t) with so-called heavy tails. The proposed approach is based on real distributions defined at a finite time interval. As a result of this research, a methodology has been developed to accurately describe the process of packet arrival at the input of the multiservice node. The proposed methodology is based on analytical methods. It guarantees error minimization when investigating the probabilistic characteristics of a switching node in a multiservice network

HARDWARE- AND INTERFERENCE-LIMITED COGNITIVE IOT RELAYING NOMA NETWORKS WITH IMPERFECT SIC OVER GENERALIZED NON-HOMOGENEOUS FADING CHANNELS

Internet-of-Things (IoT) technology has received much attention due to its great potential to interconnect billions of devices in a broad range of applications. IoT networks can provide high-quality services for a large number of users and smart objects. On the other hand, massive connectivity in IoT networks brings problems associated with spectral congestion. This issue can be solved by applying cognitive radio (CR) and non-orthogonal multiple access (NOMA) techniques. In this respect, this paper studies the performance of cooperative CR-NOMA enabled IoT networks over a generalized α − µ fading channel model. Closed-form analytical expressions of the end-to-end outage probability (OP) for the secondary NOMA users are derived using the Meijer’s G-function with a consideration of the impacts of the interference temperature constraint, primary interference, residual hardware impairments and imperfect successive interference cancellation. Moreover, to acquire some useful insights on the system performance, asymptotic closed-form OP expressions are provided. Additionally, the impact of α and µ fading parameters on the outage performance is examined and, as a result, it is concluded that the system performance sufficiently improves as α and/or µ increase. Furthermore, the outage performance of the proposed system model is shown to outperform that of an identical IoT network operating on orthogonal multiple access. Finally, the provided closed-form OP expressions are validated with Monte Carlo simulations