Ali Riza Ekti

Downlink power consumption of HetNets based on the probabilistic traffic model of mobile users

Heterogeneous networks (HetNets) are considered as a standard part of the future generation of wireless networks where masses of low power, low cost smallcells (e.g., femtocells) are anticipated to support the existing macrocell networks. While HetNets are increasing the spectral efficiency and decreasing the over-the-air signaling and uplink power consumption compared to macro networks, the large scale deployment of many lightly loaded smallcells is expected to increase the downlink power consumption of the HetNets. This paper studies the impact of smallcell population on the downlink power consumption of the HetNets. In this context, we propose that the population of smallcells is strictly depending on the traffic load due to active mobile users, which is a random variable and time-varying. We derive the mathematical framework to calculate the required population of smallcells based on the probabilistic traffic models where the number of total mobile users and number of active mobile users have different probabilistic distributions such as different combinations of Binomial and Poisson distributions. The proposed method guarantees the reduction in downlink power consumption of HetNets by forcing the smallcells to turn on the sleeping mode under low and medium traffic load conditions. Several simulation results are included to illustrate the impact of traffic load dependent population of smallcells on the downlink power consumption of HetNets. Moreover, it is shown that the mathematical and simulation results are in perfect agreement.

Joint User Association and Data-Rate Allocation in Heterogeneous Wireless Networks

In this paper, the problem of joint data-rate allocation and mobile terminal (MT) assignment is investigated in a heterogeneous wireless network (HetNet) environment that consists of wireless local area network (WLAN) access points (APs) and cellular base stations (BSs) for a best-effort service. MTs are equipped with multiple radio interfaces and have multihoming capabilities. As a result, MTs can connect simultaneously to more than one wireless network (e.g., cellular network BS and WLAN AP) and aggregate the offered bandwidths from these networks to support applications with high required data rates. Unlike the existing research, to account for the MTs limited number of radio interfaces and the abundant wireless network options, the joint MT assignment and data-rate allocation problem is formulated to select the optimal subset of networks for each MT and allocate the optimal data rate share from this subset to maximize the HetNet total utility. The problem is formulated as a mixed-integer nonlinear program (MINLP), and due to its intractability and computational complexity, we transform the problem into a convex optimization problem via a binary variable relaxation approach. Based on the mathematical analysis of the problem, we present a heuristic algorithm for joint MT assignment and data-rate allocation. Numerical results demonstrate that the proposed solution achieves a near-optimal MT assignment and data-rate allocation at reduced computational complexity.

End-to-end downlink power consumption of heterogeneous small-cell networks based on the probabilistic traffic model

Heterogeneous networks (HetNets) represent a promising solution for the next generation wireless networks (NGWNs), where many low power, low cost small-cells (e.g., fem-tocells) are planned to support the existing macrocell networks to reduce the over the air signaling and uplink power consumption, and thereby enhance the spectral efficiency compared to the macro-only network. In this context, the massive deployment of many lightly loaded small-cells is anticipated to increase the downlink power consumption of the HetNets. This paper investigates the end-to-end downlink power consumption of the HetNets, which consists of the power consumed by the macrocell and small-cell base stations and the backhaul to carry the traffic from the access to the core network. The downlink power consumption depends probabilistically on the population of the active mobile users in both the macrocell and small-cell networks such that the regulating factor is referred to as active user population factor (AUPF). A mathematical framework is presented to derive AUPF by assuming that the total population of active mobile users is a random variable and has a Binomial probability distribution. The number of active users and small-cells are calculated by the proposed probabilistic traffic model which assures the reduction in downlink power consumption since it now consists of the power consumption due to the base stations and backhaul for only the active population of mobile users. This model helps to evaluate the power consumption of HetNets. The simulations results indicate that AUPF and traffic load have significant impact on the downlink power consumption of HetNets.

On the Traffic Offloading in Wi-Fi Supported Heterogeneous Wireless Networks

Heterogeneous small cell networks (HetSNet) comprise several low power, low cost (SBSa), (D2D) enabled links wireless-fidelity (Wi-Fi) access points (APs) to support the existing macrocell infrastructure, decrease over the air signaling and energy consumption, and increase network capacity, data rate and coverage. This paper presents an active user dependent path loss (PL) based traffic offloading (TO) strategy for HetSNets and a comparative study on two techniques to offload the traffic from macrocell to (SBSs) for indoor environments: PL and signal-to-interference ratio (SIR) based strategies. To quantify the improvements, the PL based strategy against the SIR based strategy is compared while considering various macrocell and (SBS) coverage areas and traffic–types. On the other hand, offloading in a dense urban setting may result in overcrowding the (SBSs). Therefore, hybrid traffic–type driven offloading technologies such as (WiFi) and (D2D) were proposed to en route the delay tolerant applications through (WiFi) (APs) and (D2D) links. It is necessary to illustrate the impact of daily user traffic profile, (SBSs) access schemes and traffic–type while deciding how much of the traffic should be offloaded to (SBSs). In this context, (AUPF) is introduced to account for the population of active small cells which depends on the variable traffic load due to the active users.

Analysis of mobility impact on interference in cognitive radio networks

Abstract Cognitive radio (CR) technology seems to be a promising candidate for solving the radio frequency (RF) spectrum occupancy problem. CRs strive to utilize the white holes in the RF spectrum in an opportunistic manner. Because interference is an inherent and a very critical design parameter for all sorts of wireless communication systems, many of the recently emerging wireless technologies prefer smaller size coverage with reduced transmit power in order to decrease interference. Prominent examples of short-range communication systems trying to achieve low interference power levels are CR relays in CR networks and femtocells in next generation wireless networks (NGWNs). It is clear that a comprehensive interference model including mobility is essential especially in elaborating the performance of such short-range communication scenarios. Therefore, in this study, a physical layer interference model in a mobile radio communication environment is investigated by taking into account all of the basic propagation mechanisms such as large- and small-scale fading under a generic single primary user (PU) and single secondary user (SU) scenario. Both one-dimensional (1D) and two-dimensional (2D) random walk models are incorporated into the physical layer signal model. The analysis and corresponding numerical results are given along with the relevant discussions.

On the Evolution of Interference in Time for Cellular Mobile Radio Networks

In this study, the behavior of interference is investigated for cellular mobile radio networks. More explicitly, this work focuses on examining how interference evolves with respect to time under long and short term fading together for the uplink of an FDD system. The results show that decorrelation distance of shadowing plays a crucial role in predicting future interference conditions. Given the initial interference measurement, it is shown that the future interference levels are highly dependent on maintaining the decorrelation distance through the observation interval. On the one hand, if the observation interval is kept too short in a mobile environment, then a drastic deviation in the new interference level from the previous one is not expected. On the other hand, if the observation interval is kept too long, then spatial correlation of shadowing loses its significance and drastic deviations are more likely in the new interference levels; furthermore, path loss might dominate the interference status due to longer displacements.

A Survey of Machine Learning Algorithms and Their Applications in Cognitive Radio

Cognitive radio (CR) technology is a promising candidate for next generation intelligent wireless networks. The cognitive engine plays the role of the brain for the CR and the learning engine is its core. In order to fully exploit the features of CRs, the learning engine should be improved. Therefore, in this study, we discuss several machine learning algorithms and their applications for CRs in terms of spectrum sensing, modulation classification and power allocation.

K-tier heterogeneous small-cell networks: Towards balancing the spectrum usage and power consumption with aggressive frequency reuse

Heterogeneous small-cell networks (HetSNets) are considered as a standard part of the future mobile networks where multiple low-power, low-cost base stations (e.g., femtocells) complement the existing macrocell infrastructure. In this paper, we propose a heterogeneous network where multiple tiers of small-cells are deployed which in turn expand the network coverage and increase the frequency reuse distance without compromising the frequency reuse factor. The resultant network is referred to as K-tier HetSNets, where small-cells are padded between the macrocells such that each of the macrocells in the network employs aggressive frequency reuse scheme, i.e., same set of frequencies is used in each macrocell. It has been shown that the co-channel interference due to neighboring macrocells has been reduced significantly without increasing the frequency reuse factor. The large scale deployment of the small-cells may increase the downlink power consumption of the considered HetSNet. Therefore, we show that the population of small-cells in each of the K-tiers is probabilistically dependent on the traffic load due to active mobile users, such that the small-cells in the network turn on their sleep mode under low and medium traffic load during the day. Several simulation results are included to illustrate the impact of the aggressive frequency reuse scheme and traffic load dependent population of small-cells on the system interference and downlink power consumption of the small-cell base stations.

Monitoring, Surveillance, and Management of the Electromagnetic Spectrum: Current Issues in Electromagnetic Spectrum Monitoring

This paper discusses the current aspects of the surveillance and management of the electromagnetic spectrum under various topics that are vital to wireless communications. On the basis of the recent technological advancements in conjunction with the discussions on the global approaches toward electromagnetic spectrum monitoring, the paper addresses short-, medium-, and long-term strategies in wireless communications for monitoring, governing, and managing the electromagnetic spectrum of leading countries and multinational organizations. Furthermore, it proposes a novel spectrum monitoring strategy for next-generation wireless systems and outlines the implications of the proposed strategy.

The A, C, G, and T of Genome Assembly.

Genome assembly in its two decades of history has produced significant research, in terms of both biotechnology and computational biology. This contribution delineates sequencing platforms and their characteristics, examines key steps involved in filtering and processing raw data, explains assembly frameworks, and discusses quality statistics for the assessment of the assembled sequence. Furthermore, the paper explores recent Ubuntu-based software environments oriented towards genome assembly as well as some avenues for future research.