Macro Cell Research Articles

Quality of Service Provisioning for D2D Users in Heterogeneous Networks

This paper investigates power allocation for D2D communications in a Heterogeneous Network (HetNet) which includes a macro cell and pico cells, whereas femto cells are distributed inside. The objective is to minimize the total power consumption of D2D transmitter while satisfying a set of Quality of Service in D2D receivers and cellular users communication interference. To this end, we first obtain expression for the formula of signal to interference plus noise ratio (SINR) and spectral efficiency of each D2D receiver. Then, an optimization problem is formulated to minimize the total transmit power of D2D transmitters subject to QoS constraints. It is shown that this optimization problem is linear programming and it can be solved in polynomial time with standard tools. In addition, the maximization value of D2D pair transmission rates are determined with fixed cellular users parameters.

Heterogeneous network optimization using robust power-and-resource based algorithm

<p>In order to meet the increasing mobile data-traffic, spatial densification of network with several low-power nodes, the high-power macro BS and HetNet are the major key enabling solution. However, the HetNet is unplanned in nature, causes irregularities and interferences that without any user association rules. The appropriate deployment of the femto-cell in HetNet can provide effective traffic offloading, where the alleviate mobbing in the macro-cells can decrease the power consumption therefore it optimizes the user experience. Moreover, the protection is also important for the macro and femto cell users in a network through maintaining the min-max level of interferences. In this paper, we proposed RPRA that comprises two robust approach such as robust power-controller and the robust channel-allocation approach, which can improve the spectral efficiency and user experiences at lower network coverage areas via eliminating the week coverage zones. Also provide high user rate connection by effective interference in an efficient spectrum, lowering in transmission power and cost-effectiveness via less time delay. To show the effectiveness of our proposed model we have compared with several existing techniques and we got significant improvement in throughput, also reduction in time delay and transmission power.</p>

Delay Analysis in Full-Duplex Heterogeneous Cellular Networks

Heterogeneous networks (HetNets) as a combination of macro cells and small cells are used to increase the cellular network's capacity, and present a perfect solution for high-speed communications. Increasing area spectrum efficiency and capacity of HetNets largely depends on the high speed of backhaul links. One effective way that is currently utilized in HetNets is the use of full-duplex (FD) technology that potentially doubles the spectral efficiency without the need for additional spectrum. On the other hand, one of the most critical network design requirements is delay, which is a key representation of the quality of service in modern cellular networks. In this paper, by utilizing tools from the stochastic geometry, we analyze the local delay for downlink channel, which is typically defined as the mean number of required time slots for a successful communication. Given imperfect self-interference cancellation in practical FD communications, we utilize duplex mode (half-duplex (HD) or FD) for each user based on the distance from its serving base station. Further, we aim to investigate the energy efficiency for both duplexing modes, i.e., HD and FD, by considering local delay. We conduct extensive simulations to validate system performance in terms of local delay versus different system key parameters.

Secure UAV Communication Networks over 5G

Wireless communications can leverage UAVs to provide ubiquitous connectivity to different device types. Recently, integrating UAVs into a macro cell network is drawing unprecedented interest for supplementing terrestrial cellular networks. Compared with communications with fixed infrastructure, a UAV has salient attributes, such as easy-to-deploy, higher capacity due to dominant LoS communication links, and additional design degree-of-freedom with the controlled mobility. While UAV communication offers numerous benefits, it also faces security challenges due to the broadcasting nature of the wireless medium. Thus, information security is one of the fundamental requirements. In this article, we first consider two application cases of UAVs (i.e., a UAV as a flying base station and a UAV as an aerial node) in conjunction with safeguarding the exchange of confidential messages. Then, we demonstrate physical layer security mechanisms via two case studies to ensure security, and numerically show superior performance gains. Finally, we shed light on new opportunities in the emerging network architecture that can serve as a guide for future research directions.

Uplink Performance Enhancement Through Adaptive Multi-Association and Decoupling in UHF-mmWave Hybrid Networks

The rapid increase of wireless applications and services coupled with the arrival of 5G and Internet of Things will not only exacerbate demand for further capacity at the downlink (DL) but also crucially at the uplink (UL). One of the most potential enablers to simultaneously optimize both links is the DL/UL decoupling (DUDe) technique which does so by exploiting the possibility of associating each user to a different base station (BS) in each link direction. Moreover, the increasing desire to incorporate millimeter-wave (mmWave) communications in future networks further enriches the possibilities to achieve higher capacities. To this end and in contrast to existing works which use dual association based on minimum path-loss (Min-PL), this paper investigates the merits of adopting capacity-based multi-association in ultra-high frequency (UHF) and mmWave hybrid networks, where mobile users may simultaneously connect to multiple UHF small cells (SCells), millimeter-wave SCells and/or UHF macro cells (MCells). It will be shown that, our joint association and resource management approach can provide higher data rates and energy efficiency than many benchmark techniques. To achieve an insight into the performance of the proposed design, the results present a comprehensive comparison based on single and multi-connectivity as well as coupled and decoupled association for a variety of important metrics.

When QoE meets learning: A distributed traffic-processing framework for elastic resource provisioning in HetNets

In heterogeneous networks (HetNets), dynamics of user requirements across the temporal domain lead to the order of magnitude traffic to be processed by macro cells. To achieve high quality of experience (QoE) for users and to perform resource allocation for cells intelligently, we first propose a distributed traffic-processing framework (SDVTS) for elastic resource partitioning, to accommodate dynamics from the user-centric and resource-oriented perspectives respectively. Assisted by a software defined infrastructure, SDVTS fulfills the responsibilities of the request-based and push-based services in an interactive loop. Second, we formulate a traffic-processing time model that computes the delay of handling traffic. The non-convex model is decomposed and a dual evolution algorithm is explored to approximate the optimal solution. Furthermore, we introduce a low-complexity reinforcement learning algorithm with the personalized QoE profiling. A distributed algorithm in coalition between user and cell is designed for seamless connection of an advanced reinforcement learning system (ARLS) components and engines embedded in SDVTS. Extensive simulation results with thorough analysis demonstrate that our framework SDVTS dominates in terms of QoE and cell′s system performance when compared with competing approaches.

Techno-economic framework for dynamic operator selection in a multi-tier heterogeneous network

Tremendous growth of the mobile network market driven by technology evolution requires a corresponding paradigm shift of the economic aspects of mobile networks. The high heterogeneity and flexibility of 5G mobile networks have led operators to shift their business models towards an open spectrum market. In this paper, we first introduce a comprehensive techno-economic framework to investigate a heterogeneous network (HetNet) that consists of two operators: a macro cell operator and a small cell operator, operating in conditions of an open spectrum market. Both operators coexist in such a way that the small cell operator leases the spectrum from the macro cell operator. In contrast to other similar studies, in our framework, we apply the concept of evolutionary stable equilibrium (ESE), which provides some level of intuition to the behaviour of the operators. In addition, we implement the method of dynamic service selection by the end users based on a utility function, which is sensitive to both the service price and the expected throughput. To analyse the techno-economic performance of the system, we develop a real-world simulation model that encompasses a 3D urban environment using real network topology from the OpenCellID database; this model includes a large number of end users with realistic mobility patterns. The simulation results show that, from the user’s perspective, the network switching mode provides better service at a lower price due to high market competition. From the view of the operator, the most profitable mode is the static contract because there is stable service demand regardless of the price. The multi-homing mode is a promising intermediate solution that can satisfy both the end users and the operators.

Secrecy Outage Analysis of Non-Orthogonal Spectrum Sharing for Heterogeneous Cellular Networks

In this paper, we investigate physical-layer security for a heterogeneous cellular network consisting of a macro cell and a small cell in the presence of a passive eavesdropper that intends to tap both the macro-cell and small-cell transmissions. Both the orthogonal spectrum sharing (OSS) and non-orthogonal spectrum sharing (NOSS) are considered for the heterogeneous cellular network. The OSS allows the macro cell and small cell to access a given spectrum band in an orthogonal manner, whereas the NOSS enables them to access the same spectrum simultaneously and mutual interference exits. As a consequence, we present two NOSS schemes, namely the interference-limited NOSS (IL-NOSS) and interference-canceled NOSS (IC-NOSS), where the mutual interference is constrained below a tolerable level in the IL-NOSS through power control and the IC-NOSS scheme exploits a specially-designed signal for canceling out the interference received a legitimate cellular user while confusing the passive eavesdropper. We derive closed-form expressions for an overall secrecy outage probability of the OSS, IL-NOSS, and IC-NOSS schemes, which take into account the transmission secrecy of both the macro cell and small cell. We further characterize the secrecy diversity of OSS, IL-NOSS and IC-NOSS schemes through an asymptotic secrecy outage analysis in the high signal-to-noise ratio region. It is shown that the OSS and IL-NOSS methods obtain the same secrecy diversity gain of zero only, and a higher secrecy diversity gain of one is achieved by the IC-NOSS scheme. Additionally, numerical results demonstrate that the IC-NOSS scheme significantly performs better than the OSS and IL-NOSS methods in terms of the overall secrecy outage probability.

Joint Power and Bandwidth Allocation for Energy-Efficient Heterogeneous Cellular Networks

This paper investigates the problem of energy efficiency maximization (EEM) for the small cells that coexist with a macro cell in an underlay heterogeneous cellular network, where a macro base station and a number of small base stations transmit signals to a macro user and small users through their shared spectrum. We propose a joint power and bandwidth allocation (JPBA) scheme for the sake of maximizing the energy efficiency (EE) of small cells under the constraint of a guaranteed quality-of-service requirement for the macro cell. Considering that our formulated EEM-based JPBA (EEM-JPBA) problem is non-convex, we convert the original fractional problem into an equivalent subtractive form by adopting the Dinkelbach’s method, which is addressed through the augmented Lagrange multiplier approach. Moreover, a new two-tier iterative algorithm is presented to obtain the optimal solution of our EEM-JPBA scheme. Simulation results demonstrate that the proposed two-tier iterative algorithm can quickly converge to the optimal EE solution. In addition, it is shown that the proposed EEM-JPBA scheme significantly outperforms the conventional power and bandwidth allocation methods in terms of their EE performance.

Low-Latency Communications for Community Resilience Microgrids: A Reinforcement Learning Approach

Machine learning and artificial intelligence (AI) techniques can play a key role in resource allocation and scheduler design in wireless networks that target applications with stringent QoS requirements, such as near real-time control of community resilience microgrids (CRMs). Specifically, for integrated control and communication of multiple CRMs, a large number of microgrid devices need to coexist with traditional mobile user equipments (UEs), which are usually served with self-organized and densified wireless networks with many small cell base stations (SBSs). In such cases, rapid propagation of messages becomes challenging. This calls for a design of efficient resource allocation and user scheduling for delay minimization. In this paper, we introduce a resource allocation algorithm, namely, delay minimization Q-learning (DMQ) scheme, which learns the efficient resource allocation for both the macro cell base stations (eNB) and the SBSs using reinforcement learning at each time-to-transmit interval (TTI). Comparison with the traditional proportional fairness (PF) algorithm and an optimization-based algorithm, namely distributed iterative resource allocation (DIRA) reveals that our scheme can achieve 66% and 33% less latency, respectively. Moreover, DMQ outperforms DIRA, and PF in terms of throughput while achieving the highest fairness.

Enhancing Cell Throughput & Area Spectral Efficiency Using Two Level Soft Frequency Reuse Technique

Heterogeneous networks consist of different characteristics of networks like small cells having low power deployed along with macro cells having high power. Interference is the major issue to degrade the quality of signal in the heterogeneous networks. Number of interference coordination techniques are implemented to minimize interference. One of the interference coordination technique is fractional frequency reuse (FFR) and soft frequency reuse (SFR). In this paper two level Soft Frequency Reuse technique is implemented along with sectors. Parameters such as area spectral efficiency and cell edge throughput are calculated and compared with conventional FFR and Multi-level FFR technique with 6 sectoring. Better results are analyzed while simulating in the network model. Cell edge throughput improved to 54 Mbps, average cell throughput improved to 667 Mbps, peak data throughput improved to 76.7 Mbps and area spectral efficiency improved to 70.3 bits/sec/Hz/cell.

Interference Mitigation and Power Allocation Scheme for Downlink MIMO–NOMA HetNet

In this paper, a novel interference mitigation and power allocation (PA) scheme is investigated for downlink non-orthogonal multiple access (NOMA) with multiple input multiple output (MIMO) technology in heterogeneous networks (HetNets). The proposed scheme, named PA based interference alignment and coordinated beamforming (PA-IA-CB), consists of two stages. The first stage applies two steps of IA-CB; one step for canceling the inter-cluster and the co-tier interference among small cells, whereas the other step deals with the inter-cluster interference within the macro cell. In the second stage, the cross-tier interference is proposed to be managed by properly handling the allocated power to the macro base station (MBS) and the small base stations (SBSs). The PA problem is modeled as a non-cooperative game between the MBS and the SBS with the aim of increasing the system sum rate. Simulation results verify the efficiency of the proposed technique in terms of total system sum rate and outage probability compared to the conventional schemes.

Estimation of azimuth of a macro cell through user data for LTE access network

The number of antennas on a site increases due to a simultaneous deployment of multi-band and multi-mode radios to combat extremely growing data demand in the network. The correct values of physical parameters of antennas, including azimuth, height and tilt, are essential to optimize the radio frequency (RF) network automatically. It is seen that poor results in RF network optimization are mainly due to incorrect azimuth. The proposed algorithm can estimate the azimuth of an antenna in the field using passive monitoring data from the user equipment. It has been developed to identify the correct value of azimuth without doing the field audit, which can significantly reduce the time for optimization and operational expenditure (OPEX) as well. The field trial reveals that the estimated azimuth value closely matches within ±12° range in comparison to the actual value in the field. Moreover, field results show that the same algorithm is equally applicable for urban and rural morphologies as well. It can also be automated to sanctify the physical site database with proper azimuth values at large level without introducing any kind of human error.

Coverage and rate analysis in two‐tier heterogeneous networks under suburban and urban scenarios

AbstractMassive boost in data traffic demand and inconsistent user's behavior have necessitated modern cellular networks to evolve toward heterogeneous architectural framework consisting of macro and small cells to accommodate ever‐increasing user's density. Literature survey reveals that the deployment of additional small cells can encounter the booming coverage, capacity, and QoS constraints by maintaining the overall operational cost of the network. In this paper, at first, a suitable model based on nonhomogeneous Poisson point process (NHPPP) is designed for heterogeneous wireless network (HetNet) consisting of two‐tiers eNodeBs (Macro and Small Cell), where each of the tiers is differentiated in terms of transmitting power, eNodeB density, and supported data rate. Subsequently, analytical expressions are derived for coverage probability (CP) and average rate (AR) to assess the performance of the HetNet. The contribution of the paper further lies in integrating the K‐means clustering algorithm with NHPPP to find the optimal locations of the small cell eNodeBs for extended coverage and rate improvement. The proposed model is investigated under differently dense scenarios like urban and suburban areas in India. It establishes the requisite of an optimal number of small cells along with the traditional infrastructure to maximize the performance in terms of CP and AR. Finally, the proposed integrated model is compared with the traditional homogeneous Poisson point process (HPPP) and NHPPP for coverage and rate analysis. It is observed that the K‐means clustering algorithm in integration with NHPPP overshadows both HPPP and NHPPP in terms of coverage and rate under both urban and suburban deployment scenarios.

Design and simulation of priority based dual port memory in quantum dot cellular automata

Design of dual port memory in QCA is an interesting field of study due to concurrent access of data from different ports, although the solution of the data conflict is a changeling task. However, Dual port memory design in QCA is reported in this paper. The architecture is based on the data priority. Priorities of the two ports are generated from the control logic block. Priority bit is required for conditions when the same memory location is requested by both of the ports and at least one operation is the write operation. The functionality of dual port memory is realized with concurrent access of memory array with parallel input-output data lines. Read–Write, Write–Write conflicts are resolved with a priority bit. Priority is uniquely calculated only when both the port request for same memory location access, i.e., the request for concurrent Read–Write or Write–Write operation. When the same memory location is selected, only the signal of the prior port is allowed and of other port is discarded. While the read operation is requested for both the port at same or different memory locations, have no data conflicts and both the ports are allowed to perform read operation. In the proposed architecture, to overcome data conflicts signals of the port having less priority are totally discarded. Significant results of Priority-based 4 × 4 dual port memory are depicted in terms of area and delay. The area, delay, and energy dissipation of Dual port QCA SRAM macro cell are 0.61 µm2, 2.0 clock cycles, and 393.9 meV, respectively. A comparative study of the proposed dual port memory in QCA, single port memory in QCA and dual port memory in CMOS are also performed in this work. The result explored that proposed dual port memory proportionately efficient with respect to the QCA single port memory as well as CMOS dual port memory in terms of area-delay-energy.

Online Learning for Energy Saving and Interference Coordination in HetNets

In heterogeneous cellular networks (HetNets), switching OFF small cells under low user traffic periods has been proved to be an effective energy saving strategy. However, this strategy has strong interactions with interference coordination (IC) mechanisms, making it convenient to address both tasks simultaneously. The motivation of this paper is to develop a self-optimization algorithm capable of jointly controlling energy saving and IC mechanisms using an online learning approach. Our proposal is based on a contextual bandit formulation that, among other challenges, implies discovering the most energy-efficient control actions while satisfying a predefined level of Quality of Service (QoS) for the users. We propose a two-level framework comprising a global controller, in charge of a group of macro cells, and multiple local controllers, one per macro cell. The global controller implements a novel algorithm, referred to as the Bayesian Response Estimation and Threshold Search (BRETS), that is capable of learning, for each control action, its feasibility boundaries in terms of QoS and its energy consumption as a function of the aggregated user traffic. The algorithm comes with a bound on its expected convergence time. The local controllers translate the control actions learned by the global controller into local decisions. Our numerical results show that BRETS is only 1% less efficient than an ideal oracle policy, clearly outperforming other benchmark algorithms.

Game Theoretical Secure Caching Scheme in Multihoming Edge Computing-Enabled Heterogeneous Networks

Caching contents on edge computing-enabled small cell base stations (ECSBSs) has become a promising technology for mitigating burdens of macro cell base stations and offloading data from mobile users. However, as ECSBSs may be malicious, providing a secure caching scheme becomes a challenge. In this paper, we propose a novel secure caching scheme in heterogeneous networks for multihoming users. First, to provide the cached contents, a trust mechanism is designed to verify the reliability of each ECSBS. Then, in order to guarantee the integrity of cached contents and preserve the privacy of mobile users, a Chinese remainder theorem-based privacy preservation protocol is proposed. Next, we investigate the interactions among mobile users and ECSBSs by Stackelberg game, where the trusted ECSBSs are selected to provide caching resources for mobile users with multihoming access. In addition, we analyze the Stackelberg equilibrium to jointly maximize the utilities of ECSBSs and mobile users. Extensive simulations validate the efficiency of the proposed scheme with the reliability and effectiveness to cache contents.

PSO-based Resource Allocation in Software-Defined Heterogeneous Cellular Networks

A heterogeneous cellular network (HCN) is useful to increase the spectral and energy efficiency of wireless networks and to reduce the traffic load from the macro cell. The performance of the secondary user equipment (SUE) is affected by interference from the eNodeB (eNB) in a macro cell. To decrease the interference between the macro cell and the small cell, allocating resources properly is essential to an HCN. This study considers the scenario of a software-defined heterogeneous cellular network and performs the resource allocation process. First, we show the system model of HCN and formulate the optimization problem. The optimization problem is a complex process including power and frequency resource allocation, which imposes an extremely high complexity to the HCN. Therefore, a hierarchical resource allocation scheme is proposed, which including subchannel selection and a particle swarm optimization (PSO)-based power allocation algorithm. Simulation results show that the proposed hierarchical scheme is effective in improving the system capacity and energy efficiency.

Interference mitigation in heterogeneous networks with simple dirty paper coding

In heterogeneous networks where macro cells and metro cells use the same frequency band to communicate with their respective users, the major problem limiting performance is the interference caused by macro cells to metro cells. The information theoretic result known as dirty paper coding provides a way to address this problem and significantly improve the performance of heterogeneous networks with co-channel deployment. In this paper, we show how a simple dirty paper coding scheme employing Tomlinson-Harashima pre-coding with partial interference pre-subtraction can be employed by metro cells to mitigate the interference caused by macro cells. A performance study included in this paper shows that the proposed dirty paper coding scheme can lead to significant improvement in user rate statistics.

A Two-Way Cooperative D2D Communication Framework for a Heterogeneous Cellular Network

This paper analyzes the performance of two-way OFDMA based cooperative device-to-device communication (C-D2D) framework in a heterogeneous cellular network. In the proposed work, a heterogeneous network (HetNet) is considered where the base station (BS) of the macro cell is interested in communicating with the BS of smaller cells such as micro, pico or femto cell, nested inside the macro cell. Each macro cell also consists of the number of cellular users which when given an opportunity, would like to communicate directly via D2D link. The cellular users which communicate through D2D link is defined as D2D users. Due to infrastructure failure, if no direct communication link is available between two BSs then HetNet adopts a time-slotted two-phase C-D2D protocol. Macro cell BS selects a D2D user as an amplify-and-forward (AF) two-way relay to facilitate communication between two BSs. In Phase I, both the BSs send their data over N subcarriers to the D2D transmitter (DT). Subsequently, in Phase II, DT amplifies the received signal and forward it to the BSs over D subcarriers. The remaining $$N-D$$ subcarriers are used by DT for D2D communication. Results show that the proposed analysis facilitates D2D communication in HetNet, and also improves the quality-of-service (QoS) of the BSs as compared to conventional AF protocol.