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The proposed system focuses more on maintaining D2D links as long as possible which requires an optimum resource allocation initially. Considering this as the optimization issue, this work finds a solution to solve this by proposing a method based on a hybrid optimization concept with game theory. The hybrid concept includes the hybridization of ant colony optimization and Beluga whale optimization (BWO) with a game theory known as ant Beluga with game theory based optimization (AB-GTO) for resource exchange. This enables frequent updates of interference level indicators of each link and maintains consistent links between devices. The proposed solution will be under the consideration of minimization of interference and maximum sum rate as well. The adopted AB-GTO-based REFD2DC in the LTE-A system employing AB-GTO has a high sum rate value over ACO-Game, T-REX RAN, T-REX DRAN, and T-REX CYC. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) can play a key role in meeting certain demands of cellular networks. UAVs can be used not only as user equipment (UE) in cellular networks but also as mobile base stations (BSs) wherein they can either augment conventional BSs by adapting their position to serve the changing traffic and connectivity demands or temporarily replace BSs that are damaged due to natural disasters. The flexibility of UAVs allows them to provide coverage to UEs in hot-spots, at cell-edges, in coverage holes, or regions with scarce cellular infrastructure. In this work, we study how UAV locations and other cellular parameters may be optimized in such scenarios to maximize the spectral efficiency (SE) of the network. We compare the performance of machine learning (ML) techniques with conventional optimization approaches. We found that, on an average, a double deep Q learning approach can achieve 93.46% of the optimal median SE and 95.83% of the optimal mean SE. A simple greedy approach, which tunes the parameters of each BS and UAV independently, performed very well in all the cases that we tested. These computationally efficient approaches can be utilized to enhance the network performance in existing cellular networks.

Nowadays, video streaming applications are becoming one of the tendencies driving vehicular network users. In this work, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different vehicles included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the "Dynamic Vehicular Clustering" (DVC) algorithm as a new scheme for video streaming systems over vehicular ad-hoc networks (VANET). The proposed algorithm takes advantage of the small cells concept and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)-Advanced network. Vehicles are clustered together to form dynamically ad-hoc sub-networks included in the vehicular network. The goal of our clustering algorithm is to take into account several characteristics, such as the vehicle's position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications. Based on the exceptional features of the LTE-Advanced network (small cells and wireless backhauls) the DVC algorithm is a promising scheme for video streaming services over VANET systems. Experiments were carried out with a virtual topology of the VANET network created with four clusters to implement the DVC algorithm. The results were compared with other algorithms such as Virtual Trust-ability Data transmission (VTD), Named Data Networking (NDN), and Socially Aware Security Message Forwarding (SASMF). Our algorithm can effectively improve the transmission rate of data packets at the expense of a slight increase in end-to-end delay and control overhead. [ABSTRACT FROM AUTHOR]

Owing to the variety of powerful smart mobile devices (e.g., iPhone, iPad, Android) handling a wide range of traffic including multimedia, it was recommended to use the salient features of 5G networks that have been developed for high-bandwidth applications to support robust aspects for power saving mechanisms. Furthermore, there are additional advantages in using DRX, such as over-the-air resource-saving on both the uplink and downlink to increase overall system capacity. In particular, care should be exercised for real-time services. This study focused on propose powerful power optimization modes as DRX mode and Smart DRX parameters to realize appropriate rates for power saving with the higher quality of multimedia services, as well as ensuring the effectiveness of using smart DRX short cycles and smart DRX long cycles on multimedia services and the overall performance. By using real-time OPNET Simulator 17.5, simulations results had been verified that the smart DRX mechanism is better in quality of saving compared with the other DRX modes, it also ensured that smart DRX long cycles represent a better mechanism for accessing all multimedia services in terms of standard performance criteria. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) can play a key role in meeting certain demands of cellular networks. UAVs can be used not only as user equipment (UE) in cellular networks but also as mobile base stations (BSs) wherein they can either augment conventional BSs by adapting their position to serve the changing traffic and connectivity demands or temporarily replace BSs that are damaged due to natural disasters. The flexibility of UAVs allows them to provide coverage to UEs in hot-spots, at cell-edges, in coverage holes, or regions with scarce cellular infrastructure. In this work, we study how UAV locations and other cellular parameters may be optimized in such scenarios to maximize the spectral efficiency (SE) of the network. We compare the performance of machine learning (ML) techniques with conventional optimization approaches. We found that, on an average, a double deep Q learning approach can achieve 93.46% of the optimal median SE and 95.83% of the optimal mean SE. A simple greedy approach, which tunes the parameters of each BS and UAV independently, performed very well in all the cases that we tested. These computationally efficient approaches can be utilized to enhance the network performance in existing cellular networks. [ABSTRACT FROM AUTHOR]

Relaying technology is one of the LTE-A issue that is considered the area of concern of several researches. Thus LTE-Advanced with relays uses several enhanced techniques in order to improve network performance like cell throughput enhancement and coverage extension. LTE-Advanced is considered as a real evolution of the LTE as it develops new technologies that allow to meet the proposed targets. The Radio Resource Management (RRM) mechanism and relay selection method can greatly contribute to this aim. In this paper, we jointly consider the problem of relay selection and RRM in order to improve the coverage and performance of mobile broadband wireless access service. We give a detailed description of the adopted LTE-Advanced system model with multiple user equipments assisted by one evolved Node B and multiple Relay Nodes. It is important to point out that the microcell technique is jointly adopted in the proposed RRM scheme to provide a better performance. The Microcell technique is considered as a densification approach massively employed in 5G radio access network systems like femtocell and picocell. Call admission control problem is also taken into account mainly when a minimal rate is needed to guarantee user satisfaction. By numerical results, we show that our proposed method could be a better choice for LTE-Advanced standard as it represents a trade-off between the fairness and the user throughput. [ABSTRACT FROM AUTHOR]

Pada tahun 2010 3GPP mengenalkan teknologi LTE-Advanced, teknologi yang mampu memberikan kecepatan datarates hingga 3 Gbps pada sisi downlink dan 1,5 Gbps pada sisi uplink. Salah satu fitur yang menjadi faktor bertambahnya datarates tersebut adalah dengan teknik carrier aggregation. Dalam penelitian ini diimplementasikan 2 skenario yaitu Carrier Aggregation Deployment Scenario (CADS) 2 dan 5 dengan simulasi menggunakan software Atoll 3.3.0. Perancangan dilakukan pada frekuensi 1800 MHz dengan bandwidth 15 MHz dan frekuensi 2300 MHz dengan bandwidth 20 MHz di Semarang Tengah. Untuk perancangan dilakukan perancangan jaringan baru berdasarkan acuan site eksisting LTE 1800 MHz di Semarang Tengah yang diperoleh dari salah satu subkontraktor telekomunikasi di Indonesia. Parameter yang dianalisis pada penelitian ini antara lain : RSRP, CINR, user connected dan throughput berdasarkan simulasi menggunakan software Atoll 3.3.0. Untuk perancangan dengan skenario tanpa CA diperoleh mean RSRP sebesar -84,88 dBm, mean CINR sebesar 7,64 dB, rata-rata presentase user connected 99,9 % dan mean throughput sebesar 833,19 Mbps. Kemudian pada perancangan dengan skenario CADS 2 diperoleh mean RSRP sebesar 75 dBm, mean CINR sebesar 19,97 dB, rata-rata presentase user connected 100 % dan mean throughput sebesar 1.152,2 Mbps. Dan pada perancangan dengan skenario CADS 5 diperoleh mean RSRP sebesar -71,5 dBm, mean CINR sebesar 21,89 dB, rata-rata presentase user connected 100 % dan mean throughput sebesar 1.147,3 Mbps. Berdasarkan hasil analisis pada penelitian ini didapatkan hasil perancangan jaringan terbaik yaitu menggunakan skenario CADS 5. Sehingga peracangan jaringan yang paling layak untuk diterapkan di Semarang Tengah yaitu dengan menggunakan perancangan jaringan LTE-Advanced dengan CADS 5.

Wireless networks are the preferred future access networks for both defense and civilian deployments as part of telecommunication networks. The successful implementation of long term evolution (LTE) networks and applications such as the Internet of Things (IoT) in the telecommunication infrastructure has guaranteed rates of up to 100 Mbps while supporting ultra-dense wireless access network. With the incorporation of LTE-Advanced and fifth-generation wireless protocols, the data rates are expected to reach upto 1 Gbps. Hence, there is a pertinent requirement to carry out channel measurements at sub 1 GHz, 2 GHz, and 3 GHz bands to enable the design and implementation of optimum transceivers for pico-cells of LTE and future wireless networks. For the first time measurements and comparison with standard models of channel impulse response models have also been carried out in five different terrains namely Urban, Semi-Urban, Forest, Rural, and Desert terrains in the Indian sub-continent to effectively cover a variety of deployments of future wireless access networks for defense wireless networks. [ABSTRACT FROM AUTHOR]

Long Term Evolution-Advanced (LTE-A) offers several new technologies to improve the performance of the user. However, poor received signal and interference from adjacent cells in the cell-edge area can reduce the efficiency of using individual technology. Therefore, the cell-edge users have lower throughput compared to the other users in the cell and LTE-A standard. An efficient downlink radio resource management scheme is proposed in this paper by combining the coordinated multipoint transmission and reception technique along with carrier aggregation technique to achieve higher throughput for the cell-edge user and better overall performance. The proposed method jointly transmits multiple component carriers to the cell-edge user from different cells to increase the bandwidth, strengthen the received signal, and reduce the interference while it satisfies several constraints. Modified largest weighted delay first packet scheduling algorithm is deployed for resource allocation, which takes into account the delay parameters, the probability of packet loss, and data rates of the user. The obtained system-level simulation results show that the proposed method significantly enhances the throughput performances, spectral efficiency, and fairness index, compared with the existing conventional methods. [ABSTRACT FROM AUTHOR]

Intent based networks enable auto-configuration and require low latency access to cloud platforms. The use of cloud platforms incurs high operational costs. Low latency access can be realized by siting data centres close to subscribers. This paper proposes aquaria data centers with low operating costs and latency. In LTE, cloud platforms are normally accessed via the packet network gateway reachable via the serving gateway and mobility management entity. Aquaria data centers are sited close to LTE subscribers and accessed via the mobility management entity. This reduces the size of control packets in the LTE network. Simulations show that the proposed architecture reduces the size of control packets by up to 49.7% and 99.3% when header packets are uncompressed and compressed respectively. The delay associated with receiving configuration information is reduced by 50% on average. The channel capacity is enhanced by up to 22.8% on average. [ABSTRACT FROM AUTHOR]

This article presents a procurement-based user association scheme for LTE-advanced HetNets. The proposed scheme enables LTE macrocell (LMC) to leverage capacity from femtocells (FCs) and fulfill the excess demand of the registered LMC (rLMC) users. Additionally, we propose an energy-efficient and quality- of-service (QoS)-ensured resource allocation scheme for rLMC users. Although the existing solutions capacitate 2G/3G-based cellular networks to leverage resources from complementary networks, such as WiFi, they are not well suited for LTE-advanced networks because of the different architectures. Moreover, the existing solutions are centered on rate-adaptive resource allocation, which is limited in capability of offering guaranteed bit rate (GBR) services to the rLMC users. The proposed scheme has manifold notable features. First, unlike the existing solutions, it implicitly ensures QoS of offloaded rLMC users. Second, it encourages competition among FCs, which results in cost-effective user association for LMC. Third, it is adaptive to the stochastic nature of users’ demands. Finally, for data rate calculation, we use lookup tables in 3GPP standards for LTE-advanced. This makes the approach practically implementable in LTE-advanced HetNets. Numerical simulations of the proposed solution and the corresponding insights of the results justify the suitability of the proposed scheme for LTE-advanced HetNets. [ABSTRACT FROM AUTHOR]

The purpose of LTE-A technology is to provide high spectral efficiency, lower delay and stronger intercell interference control for a multi- user environment. The architecture of LTE basically contains E-UTRAN and evolved packet core. E-UTRAN is the combination of UE and ENodeB (enhanced node B) used to control the radio network. EPC provide end to end connection and backward capability with previous networks. Major entities included in EPC are P-GW, S-GW, HSS and MME. This new architecture fulfil the requirement of next-generation mobile networks for high connectivity and multiple type of networks. Heterogeneous network is one of them in which different power base stations like femtocell, picocell, and radio remote head deployed in a geographical area with in macrocell cell. It is one of the cost effective solution to provide high throughput and spectral efficiency and fairness for cell edge user. Deployment of femtocell improved the data rate and coverage in small regions like office, home, shopping mall and dense areas. Along with this an efficient fair sharing of resource allocation plays an important role in improving the performance of networks. This paper analysed the performance of round robin, resource fair, Max-throughput, best CQI and proportional fair LTE-A resource scheduling techniques on homogeneous networks. For heterogeneous networks a new cluster based proportional fair resource scheduling technique is proposed, which provides an efficient resource to the most sufferer user and improved fairness and cell edge user throughputs. In heterogeneous networks multiple femto cell were deployed in macro cell area. Access policies are applied on open and closed group. The performance is measured in terms of cell edge throughputs, peak throughputs, average throughputs, wideband SINR, spectral efficiency, and fairness index for homogeneous, heterogeneous networks and for user mobility. The performance result showed that Best CQI and MaxTP scheduler outperforms in throughput level and attains highest average cell throughput of 83 Mbps and UE average throughput of 20 mbps in homogeneous networks and approximately 43 Mbps in heterogeneous networks. Comparative result in heterogeneous network indicates that the proposed scheduler increases 2% gain in fairness and 1–1.89% gains in edge throughputs with respect to proportional fair scheduler and allocates 79% fair share resources among UE. Round robin scheduler delivered very poor throughput and fairness index in both homogeneous and heterogeneousnetworks. [ABSTRACT FROM AUTHOR]

A LTE-advanced heterogeneous network consists of many macrocells, and within each macrocell, there can have many picocells and user equipments (UEs). A UE within a macrocell can request resource blocks (RBs) from either the macrocell or a picocell within the macrocell. In this paper, two optimal problems are defined for the association of UEs, RBs, and heterogeneous cells. We show that both problems are equivalent to a 0/1 knapsack problem and, therefore, can be solved in pseudo-polynomial time by dynamic programming. Based on above two optimal problems, we, then, propose a cell selection and resource allocation (CSRA) scheme to solve the problem of allocating a UE to its macrocell or to a picocell within the macrocell. The design goal of picocells is to unload the traffic for the macrocell. When there are available RBs and UEs within the picocell, the CSRA scheme offloads UEs to the picocell to release the most number of RBs for the macrocell. Only when there are not enough RBs within a picocell and there are available RBs within the macrocell, for load balancing, the CSRA scheme moves some UEs to the macrocell. The CSRA scheme stops whenever the picocell is not overloaded or the macrocell does not have available RBs. Simulation results show that our proposed scheme performs better than the cell range expansion scheme in terms of goodput, loss rate, and delay.

Long-Term Evolution-Advanced (LTE-A) networks have been regarded as having great potential to support the Internet of Things (IoT). However, the high probability of preamble collisions when massive numbers of IoT devices try to access the network within a short period has become a significant problem. In this paper, we propose a new scheme to efficiently handle the initial access contention for massive numbers of IoT devices in LTE-A networks. The proposed scheme divides an entire preamble set into $k$ subgroups; then, contention resolution is performed in each subgroup independently in a parallel and pipelined manner. Simulation results show that our scheme leads to considerable improvement in terms of average access delay and standard deviation of access delays without increasing blocking probability. Moreover, utilization of preamble resources is greatly improved by reducing the number of random access slots, where only a few devices participate in preamble selection.

Through analyzing the random access model of slotted access based channel access control protocol (SCACP) in LTE-Advanced system, an optimization algorithm for access frame length selection based on slotted access was proposed. The dynamic frame length selection in slotted access based on network real-time access load was realized. Moreover, the optimized access frame length was more suitable for current access load than before. It could ensure a high success rate of access, eliminate the unnecessary access delay and decrease the number of retransmissions to some extent. The simulation results demonstrate that the proposed dynamic frame length selection algorithm is more effective and practical.

ABSTRAK Penerapan teknologi Long Term Evolution (LTE) di Indonesia belum optimal dalam pengalokasian spektrum dikarenakan keterbatasan spektrum, untuk mengatasi masalah tersebut 3GPP mengeluarkan teknologi terbaru yaitu LTEAdvanced yang mendukung fitur carrier aggregation (CA) yang memberikan throughput yang lebih tinggi dengan penggunaan spektrum yang lebih efisien. Pada penelitian ini dilakukan perencanaan jaringan LTE-Advanced menggunakan metode inter-band CA dengan menggabungkan dua band frequency yang berbeda yaitu bandwith 5 MHz di band 5 (850 MHz) dan bandwidth 10 MHz di band 3 (1800 MHz). Untuk mendapatkan performansi yang maksimal perencanaan jaringan LTE dan LTE-A dikombinasikan dengan penggunaan skema Physical Cell Identity (PCI) dan Soft Frequency Reuse (SFR). Penggunaan PCI meningkatkan SINR sebesar 1 dB dan throughput meningkat sebesar 200 Kbps, sedangkan penggunaan skema SFR meningkatkan SINR sebesar 9 dB dan throughput meningkat sebesar 13 Mbps. Kata kunci: LTE-Advanced, PCI, SFR, Carrier Aggregation. ABSTRACT The implementation of Long Term Evolution (LTE) technology in Indonesia has not been optimal due to spectrum limitations. To overcome the problem, 3GPP issued the latest technology, i.e. LTE-Advanced, to support the carrier aggregation (CA) feature that provides higher throughput with more efficient spectrum usage. In this study, LTE-Advanced network planning was performed using the inter-band CA method by combining two different band frequencies, namely 5 MHz bandwidth on Band 5 (850 MHz) and 10 MHz bandwidth on Band 3 (1800 MHz). In addition, to generate maximum performance, the LTE and LTEA networks planning was combined with the use of Physical Cell Identity (PCI) and Soft Frequency Reuse (SFR) schemes. The use of the PCI managed to increase SINR by 1 dB and throughput by 200 Kbps, while the use of SFR scheme managed to increase SINR by 9 dB and throughput by 13 Mbps. Keywords: LTE-Advanced, PCI, SFR, Carrier Aggregation.

A wideband hybrid Envelope tracking (ET) modulator utilizing a hysteretic-controlled three-level switching converter (3L-SWC) and a slew-rate enhanced linear amplifier (LA) are presented. In addition to smaller ripple and lower losses of 3L-SWCs, employing the proposed hysteresis control loop results in a higher speed loop and wider bandwidth converter, enabling over 80 MHz of switching frequency. A concurrent sensor circuit monitors and regulates the flying capacitor voltage $V_{\mathrm{ CF}}$ and eliminates the conventionally required calibration loop to control it. The hysteretic-controlled 3L-SWC provides a high percentage of power amplifier (PA) supply load current with lower ripple, reducing the LA high-frequency current and ripple cancellation current, improving the overall system efficiency. A slew-rate enhancement (SRE) circuit is employed in the LA, resulting in slew rate of over 307 V/ $\mu \text{s}$ and bandwidth of over 275 MHz for the LA. The SRE circuit provides a parallel auxiliary current path directly to the gate of the class-AB output stage transistors, speeding-up the charging or discharging of output without modifying the operating point of the remaining LA, while maintaining the quiescent current of the class-AB stage. The supply modulator is fabricated in a 65-nm CMOS process. The measurement results show the tracking of long-term evolution (LTE)-40-MHz envelope with 93% peak efficiency at 1-W output power, while the SRE is disabled. Enabling the SRE, it can track LTE-80-MHz envelope with peak efficiency of 91%. [ABSTRACT FROM AUTHOR]

Since the basic objective of all communication systems is to provide a high-quality performance, the development of effective retransmission schemes with incremental redundancy has gained significant importance recently. In this regard, two retransmission mechanisms had been addressed the hybrid-automatic repeat request (HARQ) and the new smart hybrid-automatic repeat request (SHARQ); thus, SHARQ is integrated with an autonomous retransmission method, ensuring the transmission of a data packet regardless to the successful decoding of the packet at the receivers. That is to say, in order to make sure of having a maximum spectral efficiency, this mechanism determines the required optimal number of autonomous retransmissions. In other words, the developed system means to guarantee the benefits of the SHARQ mechanism based on the LTE-A network as well as the output improvement from the SHARQ. Furthermore, in this current research paper, according to a new proposed algorithm a comparison will provided between the most two basic newest retransmission mechanisms over the LTE-A. Thus, through the use of the OPNET Simulator 17.5, it found out that the SHARQ mechanism is much better for the system's operation, compared to the HARQ mechanism; not to mention that it is the best choice for all multimedia services as well as the overall network performance. [ABSTRACT FROM AUTHOR]

In this paper, an Adaptive Handover Margin algorithm based on Novel Weight Function (AHOM-NWF) is proposed through Carrier Aggregation operation in Long Term Evolution—Advanced system. The AHOM-NWF algorithm automatically adjusts the Handover Margin level based on three functions, f (S I N R) , f (T L) and f (v) , which are evaluated as functions of Signal-to-Interference-plus-Noise-Ratio (SINR), Traffic Load (T L) , and User's velocity (v) respectively. The weight of each function is taken into account in order to estimate an accurate margin level. Furthermore, a mathematical model for estimating the weight of each function is formulated by a simple model. However, AHOM-NWF algorithm will contribute for the perspective of SINR improvement, cell edge spectral efficiency enhancement and outage probability reduction. Simulation results have shown that the AHOM-NWF algorithm enhances system performance more than the other considered algorithms from the literature by 24.4, 14.6 and 17.9%, as average gains over all the considered algorithms in terms of SINR, cell edge spectral efficiency and outage probability reduction respectively. [ABSTRACT FROM AUTHOR]

LTE-Advanced, the 4.5 G technology is built upon 3GPP specifications, is going to rule the wireless network world. This work proposes an energy efficient, QoS-awarescheduler for transmission of real-time data in downlink LTE-advanced networks. A basic LTE-Advanced scheduler has been developed by combining Carrier Aggregation with multi input and multi output (MIMO) features to provide the required bandwidth. We have formulated the scheduling problem as a gain of weighted transmission rates of all possible combinations of various resources required by the channel for transmitting data. The overall process of resource allocation for the downlink scheduling is then optimized using fuzzy rules. The main focus of our study is the cell edge users, and so Voronoi algorithm was used for the first time in LTE-Advanced networks to detect those cell edge users.The results proves that the Carrier Aggregation with MIMO scheduling scheme is energy efficient, QoS-aware and benefits the cell edge users with increased coverage. This scheduling scheme attains excellent throughput with improved fairness for real-time data transmission among the mobile users. [ABSTRACT FROM AUTHOR]

Due to the wide proliferation of the 3GPP long term evolution (LTE) and LTE-Advanced systems as the air interface for 4th generation (4G) wireless systems and beyond, telecommunication operators became more interested in using the LTE infrastructure to meet the projected surge in demand for machine-to-machine (M2M) and IoT communications. As a result, the LTE-Advanced system must evolve to provide these services as an overlay over the original network that is originally designed for human-to-human (H2H) communication. In this setup, M2M communication devices share the same random access channel (RACH) with the H2H communication devices. Since M2M communication is expected to be massive, consequently the RACH is a new bottleneck in the LTE-A system. This triggered the need to enhance the operation of the RACH to meet the needs to support the low power and low data rates of M2M devices. The current standardized scheme to request access to the system is known to suffer from congestion and overloading in the presence of a huge number of devices. Accordingly, recent research pointed to the need of designing more efficient ways to manage the random access channel in such setups. Most of previous works focused on solving the congestion problem in RACH in the presence of M2M solely, but not with the existence of both M2M and H2H services. In this work we propose a new random access channel scheme based on Q-learning approach to reduce the congestion problem. The scheme adaptively divides the available preambles between both M2M and H2H devices in a way that provides an acceptable service for the H2H devices and maximizes the number of active M2M devices. The adaptation is done based on current demand levels from both the H2H and M2M devices and the observed service levels. The results indicate that the proposed approach provides high random access channel success probability for both M2M and H2H devices even with the huge number of M2M devices. [ABSTRACT FROM AUTHOR]

At present, the revolution of the Internet of things (IoT) is an area of technology that is growing exponentially. IoT has a significant impact on consumer products and is expected to dominate in a wide variety of areas such as business, industry, and governments. In high-density deployments of IoT systems, providing sufficient networking and computing infrastructure with reliable and low-latency communication links is a challenging task. This is owing to the resource allocation methods applied at the cell edge that do not guarantee fair and efficient resource partitioning when receiving different types of IoT traffic. Deployment of an efficient and fair resource-partitioning scheme for IoT devices is necessary to reduce the effects of IoT traffic on network performance. The main contribution of this paper is to design efficient resource partitioning for different types of IoT device communications with an adaptive sharing priority (AS) scheme. Moreover, we analyze and compare the performance of conventional admission control schemes such as fixed sharing and complete sharing with our proposed scheme using a developed simulation as well as analytical modeling with a multidimensional continuous-time Markov chain. We also present and discuss the performance results of the AS scheme in terms of blocking probabilities, average waiting delay, and system utilization using different scenarios with different parameters. The results demonstrate that the AS scheme performs better than the two previously studied conventional schemes. [ABSTRACT FROM AUTHOR]

Through analyzing the access efficiency of machine type communication（MTC）devices in LTE-Advanced system,a loading-feedback control method was proposed.The current access load was estimated and the load of next access slot were calculated using the preamble state information,and the access control parameters for MTC device were adjusted based on the load change dynamically.The good performance of the proposed solution was evaluated by computer simulations.The simulation result shows that the proposed scheme can reduce the impact of nearly simultaneous access of a large number of MTC devices on human-to-human（H2H）devices,decrease the number of retransmissions and improve the access success rate effectively.

The interference is the most important problem in LTE or LTE-Advanced networks. In this paper, the interference was investigated in terms of the downlink signal to interference and noise ratio (SINR). In order to compare the different frequency reuse methods that were developed to enhance the SINR, it would be helpful to have a generalized expression to study the performance of the different methods. Therefore, this paper introduces general expressions for the SINR in homogeneous and in heterogeneous networks. In homogeneous networks, the expression was applied for the most common types of frequency reuse techniques: soft frequency reuse (SFR) and fractional frequency reuse (FFR). The expression was examined by comparing it with previously developed ones in the literature and the comparison showed that the expression is valid for any type of frequency reuse scheme and any network topology. Furthermore, the expression was extended to include the heterogeneous network; the expression includes the problem of co-tier and cross-tier interference in heterogeneous networks (HetNet) and it was examined by the same method of the homogeneous one.

All over the world, road congestion is among the most prevalent transport challenges usually in urban environments which not only increases fuel consumption and emission of harmful gases, but also causes stress for the drivers. Intelligent Transportation System (ITS) enables a better use of the infrastructure by connecting vehicles to other vehicles as well as infrastructure and thus delivers a faster communication opportunity to ensure safe and secure driving. Machine-to-machine (M2M) communication is one of the latest information and communication technologies which offers ubiquitous connectivity among several smart devices. The use of mobile (cellular) M2M communications has emerged due to the wide range, high reliability, increased data rates, decreased costs as well as easy and short-term deployment opportunities. Since the radio spectrum is a scarce resource, M2M traffic can potentially degrade the performance of mobile networks due to the large number of devices sending small-sized data. This paper presents an efficient data multiplexing scheme by using Long-Term Evolution Advanced (LTE-Advanced) Relay Nodes, which aggregates M2M traffic to maximize radio resource utilization. Extensive system-level simulations are performed using an LTE-Advanced-based model developed in the RIVERBED modeler to evaluate the performance of the proposed data multiplexing scheme. Simulation results show that approximately 40 % more smart M2M devices used in ITS and logistics are served per LTE-Advanced cell under the present system settings.