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Because the fifth-generation (5G) mobile wireless networks show promise in meeting the service requirements of Internet of Things, 5G systems must be equipped with the capacity to interconnect all existing and emerging technologies. To keep up with this challenge, heterogeneous networks (HetNets) can be deployed; in HetNets, the coverage area of a macro base station is embedded with many smaller base stations. This paper presents the architecture of a HetNet with overlapping small cells (HNOSC) for 5G IoT networks. The proposed HNOSC architecture considers the movement of user equipment (UE) and the overlapping area between any two small cells. We develop an analytical model by using a Markov chain of three states to derive a closed-form formula for the total downlink transmission power (TDTP) in terms of the radius of each small cell, size of the overlap-ping area, and UE mobility. Given the path loss factor and associated parameters of UE movement, the relationship between the coverage area of overlapping small cells and the TDTP consumption can be derived. Thus, the deployment of small base stations can be optimised to obtain the best trade-off between UE service quality and operator cost. [ABSTRACT FROM AUTHOR]

The most important feature of 3G mobile cellular network is introduction of voice data integrated service under multilayered cell environment to support overflow traffic of lower layered cells by upper ones. This paper deals with traffic model of three layered cells, i.e., micro cell, macro cell and satellite cell. Here a new call admission control is introduced for three layered cell of 3G mobile cellular network. State transition chain is designed for theoretical analysis of above mentioned traffic. Blocking probability of data call, new voice call and handover failure of voice call, probability of utilization of micro cell channel, macro cell channel and satellite cell channel are analyzed against different traffic parameters and yield logical results.

The small cell structure in which many cells are arranged per unit area by reducing the size of cells is a candidate technology for an increase in transmission capacity in the 5G environment. However, the decrease in the size of the cell led to additional problems such as increased inter cell interference and frequent cell changes owing to the movement of the terminal. Therefore, the aim of this study was to propose small cell dynamic channel allocation (SDCA) and hybrid and dynamic channel allocation (HDCA) using conventional reuse methods to improve the macro cell performance while efficiently utilizing scarce frequency resources. The proposed method facilitates an improved performance that is lacking for macro-cell users in the center area of the cell boundary for the network where conventional macro cells and small cells are superposed. Furthermore, to improve the performance, it can provide resources that are lacking in the small cells of the center. To evaluate the performance, the proposed method was compared to frequency reuse factor1 (FRF1), frequency reuse factor3 (FRF3), and fractional frequency reuse (FFR) methods in terms of the signal-to-interference/noise-ratio (SINR) of users of each macro cell and small cell, outage, capacity for each user, and total system capacity. As a result of comparing the SINR, it was confirmed that the performance of the macro cell users has improved by an average of 43.88% compared to FRF1, FRF3, and FFR, and the performance of small cell users has improved by an average of 4.31%. Comparison results show that the outage proportions of the macro and small cell users are 61.29% and 70.59% lower on average, respectively. A comparison of results show that the capacities of the macro and small cell users have also improved by 22.5% and 14.5% on average, respectively. As the comparison results of the total system capacity indicate, the proposed method shows an average improvement of 11.67%. In cases in which the added resources of the small cells are found to be unnecessary based on the results of the performance evaluation, there is an advantage in that they can be reduced to improve the performance of macro cell users, or they can be used to fill the insufficient resources of the small cells while maintaining the performance of the macro cell users. This fluidity originates from the ability to address occasional situations in a dense environment. These two approaches are expected to be used effectively in 5G network environments. [ABSTRACT FROM AUTHOR]

In a highly dense heterogeneous cellular network, the loads across cells are uneven due to random deployment of cells and the mobility of user equipments (UEs). Such unbalanced loads result in performance degradation such as throughput and handover success. In order to solve the uneven load problem for better network performance, we propose a cluster-based mobility load-balancing algorithm for heterogeneous cellular networks. Traditional mobility load balancing (MLB) schemes that consider only the adjacent neighbors cannot provide enough improvement in network performance. On the other hand, the previous MLB schemes consider neighbors in the entire network suffer from unnecessary MLB actions. However, in the load balancing process, the proposed algorithm considers overloaded cells and their neighbors within then-tiers. First, the algorithm models the network as a directed multi-graph and constructs clusters taking the overloaded cells and their n-tier neighbors. Therefore, by adjusting cell individual offset parameters of the cells in the clusters the algorithm achieves load balancing locally. Since load balancing is performed inside the clusters, the network can be optimized more efficiently by avoiding unnecessary MLB actions. Simulations show that the proposed algorithm distributes the load across the network more evenly than other MLB algorithms, and in a low UE velocity scenario, it increases the overall network throughput by 6.42% compared to a non-optimized network without an MLB algorithm.

In this paper, the impact of the network architecture on signal quality in the fourth generation of the public mobile network is analyzed. The analysis was performed using RSRP (Reference Signal Received Power), RSRQ (Reference Signal Received Quality), SINR (Signal to Interference plus Noise Ratio) and throughput parameters in indoor environment. The signal quality parameters were collected by measurement using TEMS Investigation and TEMS Pocket software. The measurements were carried out at the School of Electrical Engineering on the ground floor of the Technical Faculty building for the macro and micro cell scenario. It has been found that better signal quality is ensured in micro cells. Quality of the signal is also considered by the various services provided to the users.

In this paper, we analyze the impact of the small cell user density on the power consumption and the number of served users by the macro cell and small cells. It is assumed that users are distributed uniformly in all coverage area with different density and small cell user density is related linearly with macro cell user density. In the simulations, three different mean values are chosen, where the power consumption and the number of served users by the macro cell and small cells are investigated according to these values. The simulation results show that small cells with low mean value enable to save more power. When user density of macro cell is and mean value of small cell user density equals to 15, saved power by using the small cells sleeping technique is 695 Watts. When this saved power decreases to 372 Watts. Similarly, as the mean value of the small cell user density increases, the power gain obtained by the algorithm decreases.

Bu çalışmada, küçük hücre kullanıcı yoğunluğunun güç tüketimi ve makro ve küçük hücreler tarafından servis verilen kullanıcı sayısı üzerindeki etkisi analiz edilmektedir. Kullanıcıların tüm kapsama alanında düzgün dağılımlı olarak konumlandığı ve küçük hücre kullanıcı yoğunluğunun makro hücre kullanıcı yoğunluğu ile doğrusal olarak ilişkili olduğu varsayılmıştır. Benzetimlerde, üç farklı ortalama değer seçilmiş ve bu değerlere göre güç tüketimi ve makro hücre ve küçük hücreler tarafından servis verilen kullanıcı sayısı incelenmiştir. Benzetim sonuçları, düşük ortalama değere sahip küçük hücrelerin yüksek tasarruf gücü sağladığını göstermektedir. Makro hücrenin kullanıcı yoğunluğu ve küçük hücre kullanıcı yoğunluğunun ortalama değeri 15 olduğunda, küçük hücre uyutma tekniği kullanılarak elde edilen kazanç 695 Watt’tır. olduğunda ise 372 Watt’a düşmektedir. Benzer olarak küçük hücre kullanıcı yoğunluğunun ortalama değeri arttıkça algoritma ile elde edilen güç kazancı azalmaktadır.

Recently, the need for user data rate traffic has increased for running high-bandwidth applications. Therefore, the way forward lies in 5G heterogeneous cellular networks. The 5G network is comprised of two network hierarchies. As the first hierarchy, there are MBSs with large macro cells for macro users. As the second hierarchy, there are FBSs referred to as small cells for femto users. The 5G networks encourage the use of large macro and small cells for efficient utilisation and distribution of channel resources. In this study, the authors have proposed an efficient RF channel distribution mechanism on the basis of the current SINR levels of FUEs and MUEs. On the basis of the users’ present SINR levels, the channels will be allocated by the central MBS to MUEs and FUEs via FBSs. The major obstacle in RF channel allocation to FUEs and MUEs is cross-tier interference at the downlink channel at the MUEs and FUEs from the transmitted signals of MBSs and FBSs. In this study, an efficient RF channel allocation scheme is proposed on the basis of channel modelling constraints, which will minimise the cross-tier interference at the downlink channel at the MUEs and FUEs during RF channel allocation to FUEs and MUEs present in the same coverage area

In this paper, we analyze the impact of the small cell user density on the power consumption and the number of served users by the macro cell and small cells. It is assumed that users are distributed uniformly in all coverage area with different density and small cell user density is related linearly with macro cell user density. In the simulations, three different mean values are chosen, where the power consumption and the number of served users by the macro cell and small cells are investigated according to these values. The simulation results show that small cells with low mean value enable to save more power. When user density of macro cell is λ0 = 5x10-4 and mean value of small cell user density equals to 15, saved power by using the small cells sleeping technique is 695 Watts. When λ0 = 10x10-4 this saved power decreases to 372 Watts. Similarly, as the mean value of the small cell user density increases, the power gain obtained by the algorithm decreases. [ABSTRACT FROM AUTHOR]

In a heterogeneous network (HetNet) with ultra-dense small-cell deployment, fast-moving users may experience frequent handovers between small cells owing to the small coverage areas of those cells. Moreover, due to shadowing and channel fading, static or slow-moving users can also experience frequent handovers, called ping-pongs. Such redundant handovers are unacceptable, and can cause packet losses or packet delays leading to a poor user experience. To solve these unwanted handover problems, we propose a frequent handover mitigation algorithm for ultra-dense HetNets. Based on mobility behavior, the proposed algorithm categorizes frequent handover-experience users as either fast-moving or ping-pong users. Fast-moving users are then handed over to the macro layer, and ping-pong users are managed by adjustment of handover parameters. However, if ping-pongs cannot be avoided through handover-parameter adjustment, ping-pong users are handed over to the macro layer as well. Simulation results show that the proposed algorithm can reduce 79.56% of the overall handovers, and increase network throughput by 10.82%. [ABSTRACT FROM AUTHOR]

Deployment of small cells beside macro cells has become the promising solution to meet the increasing service demand with limited bandwidth. However, the inter- and intra-tier interference limit the network capacity. Here, we present a semi-cooperative based resource allocation (SCRA) framework for cognitive small cells. The proposed framework allocates the underutilized spectrum of primary network for the downlink transmission of cognitive small cells such that the interference to primary users is below the threshold and the QoS (Quality of Service) of the associated user is satisfied. The game theoretic approach is adapted for distributed resource allocation where players (i.e. cognitive small cells) access primary channels in a non-cooperative manner. The utility of players is modeled as a negative weighted sum of the transmission power in the primary channels. We assume that the macro cell, after a specific interval of time, uses the primary users’ cooperation to obtain the channel weights for the players. We show that there exists the Nash Equilibrium (NE) in the proposed game of resource allocation. Finally, the performance of proposed SCRA enabled two-tier networks is demonstrated through extensive simulations. [ABSTRACT FROM AUTHOR]

In heterogeneous networks, the random deployment of femto access points (FAPs) and macro base stations (MBSs) with uncoordinated channel access imposes huge intertier interferences. In real-life networks, the process of MBSs’ deployment exhibits the homogeneity; however the FAPs have the behavioral characteristic of clusters formation, such as in malls, apartments, or offices. Therefore, the composite modeling of the MBSs and the FAPs using Poisson point process and Poisson cluster process is employed for the evaluation of coverage probability. The scenario of the real-time traffic for macrotier and the best-effort traffic for femto-tier is considered. Cognition is introduced in the clustered FAPs to control the intertier interference. Furthermore, the impact of the macrotier load is analyzed by exploiting the inherent coupling between coverage probability and activity factor of an MBS. Further, we study the effect of co-channel, orthogonal, and partial spectrum sharing modes on the coverage for given parameters, such as load condition and FAPs/MBSs density. We provide simulation validation for the derived expressions of coverage and present a comparative analysis for the mentioned spectrum sharing modes. [ABSTRACT FROM AUTHOR]

The next generation of cellular networks is expected to provide huge capacity, and site densification is one of the possible solution to increase the network capacity. The target of this paper is to show the impact of macro/micro site densification and higher order sectorization on signal strength, signal quality and throughput in LTE network. It also highlights the impact of site and sector densification on the cell overlapping and cell border areas. A detailed techno-economical analysis along with area power consumption and area spectral efficiency is also provided in this paper. In site densification, the intersite distance (ISD) between the base station sites is decreased, which results in strong inter cell interference. The results presented in this paper show that the spectral efficiency of the cell decreases with the site densification. However, the average area spectral efficiency increases due to a larger number of cells in the densified network. At the same time the number of cell border users overlapped by multiple servers also increases with the site and sector densification. It is shown that in one square kilometer, increasing the number of cells from 14 (3-sector site with 500 m ISD) to 693 (6-sector site with 100 m ISD) relatively improves the area spectral efficiency by 24.5 times at the cost of 49.5 times more number of cells. Almost identical power efficiency is provided with 3-, and 6-sector site. However, a higher order sectored site was found to be more cost efficient. [ABSTRACT FROM AUTHOR]