Multi-tier Heterogeneous Networks Research Articles

SIR Meta Distribution in the Heterogeneous and Hybrid Networks

With the development of the technology, the wireless systems are becoming more heterogeneous with the introduction of various power nodes including femtocells, relays, or distributed antennas. Among the research of wireless network performance, the meta distribution of the signal-to-interference ratio (SIR) has attracted significant attention. Compared to the standard success (coverage) probability, the meta distribution provides much more fine-grained information about the network performance. In this paper, we analyze the meta distribution of the SIR in the multi-tier heterogeneous and hybrid networks, where each tier is based on a homogeneous independent Poisson point process model. For the open tiers (the users can associate with any tier) and the closed tiers (the users can only associate with a certain tier), we study the b th moment of the conditional success probability for the typical user and give the beta approximation of the meta distribution from analysis and simulations. Furthermore, we analyze the per-link rate control for open tiers and closed tiers, which answers the question: “how to set the SIR threshold to meet a target reliability?”. We give the approximate value of the SIR threshold to meet a target reliability and show how the value is related to the path loss exponent and densities.

A Multi-criteria based handover algorithm for vehicle-to-infrastructure communications

Maintaining seamless quality of service (QoS) requirements for ongoing delay sensitive applications during handover processes for Vehicle-to-Infrastructure (V2I) communication over heterogeneous networks is a challenging task. The situation becomes even more challenging to deal with for multi-tier heterogeneous networks with various network sizes. To overcome the above challenges, we propose a multicriteria-based handover algorithm for V2I communications (V2I-MHA) to be used in multi-tier heterogeneous network environments. V2I-MHA selects the most appropriate underlying target network for handover based on QoS profiles of the ongoing applications and services. Moreover, our proposed algorithm filters out the inappropriate candidate networks using a multi-criteria decision-making technique based on Simple Additive Weighting (SAW) approach. However, our approach ensures that the most appropriate candidate network for handover processes is selected not only based on QoS requirements of the ongoing applications, but also on the knowledge of candidate network parameters (e.g. bandwidth, packet latency, packet losses, and service pricing). A multi-mode vehicle On-Board Unit (OBU) containing Long Term Evolution-Advanced (LTE-A) and Wi-Fi network interface cards is developed in the Riverbed (previously OPNET) simulator for system performance evaluation. The simulation results show that the proposed V2I-MHA outperforms (in terms of handover failure rate and packet losses) the existing handover methods.

Repairable Fountain Coded Storage Systems for Multi-Tier Mobile Edge Caching Networks

Mobile edge caching (MEC) is an emerging paradigm where cloud services are extended to base stations (BSs) and devices to support a variety of applications and services in the Internet of Things (IoT). It expects to exploit storage resources deployed at different BSs and idle resources of end devices to efficiently cache and deliver contents. However, frequent mobility of devices with cached data can lead to data loss. Therefore, it becomes an important yet very challenging issue to cache the massive data with high data fault-tolerance and low cost. In this paper, we consider a multi-tier MEC network, where cloud-BS, edge-BSs and mobile devices collaboratively store and deliver contents to users. In addition, a framework based on repairable fountain codes (RFCs) with unequal repair locality (URL) for data caching, repairing and downloading, termed URL-RFC, is proposed to achieve efficient data caching in multi-tier heterogeneous MEC networks. Furthermore, a theoretical analysis and simulation results are provided to analyze and compare the energy costs of URL-RFC and existing solutions. It is demonstrated that the proposed URL-RFC scheme outperforms other redundant fault-tolerant schemes, which validates the potential value and feasibility of URL-RFC enabled storage in multi-tier MEC networks.

Optimization of base station density and user transmission power in multi-tier heterogeneous cellular systems

In this paper, a loss minimization issue is proposed, which includes both cost of user power consumption and base station (BS) deployment. A multi-tier heterogeneous network (HetNet) is considered and modeled with random geometry of Poisson point process (PPP). BSs and users are distributed randomly following PPP with the specific densities. Cutoff threshold (ρk) as the average received power at the kth tier BS is proposed to model uplink channels. The kth tier user transmission power is formulated through a channel inversion power control. Tier Selection Probability indicating the possibility of a user accessing a certain tier is derived. Bias (Bk) is proposed to change the kth tier Tier Selection Probability. Thus, an operator is able to change bias based on nearby environment and communication status. Also, Truncated Outage Probability and signal-to-interference ratio (SINR) Outage Probability are derived, which represents a connection failure status. Truncated outage results from insufficient power supply at users and SINR outage results from poor communication environment. Genetic algorithm (GA) is introduced to determine the trade off between outage constraints and the loss minimization issue. Simulation shows that, when equipped with equal bias, multi-tier network has smaller Truncated Outage Probability but larger SINR Outage Probability than single-tier network. On the contrary, with different bias, Truncated Outage Probability in multi-tier is larger than the single-tier case and SINR Outage Probability in multi-tier is less than that in single-tier. A considerable loss reduction can be witnessed in both cases.

Analysis and Optimization of Service Delay for Multiquality Videos in Multitier Heterogeneous Network With Random Caching

Aiming to minimize service delay, we propose a new random caching scheme in device-to-device (D2D)-assisted heterogeneous network. To support diversified viewing qualities of multimedia video services, each video file is encoded into a base layer (BL) and multiple enhancement layers (ELs) by scalable video coding (SVC). A super layer, including the BL and several ELs, is transmitted to every user. We define and quantify the service delay of multi-quality videos by deriving successful transmission probabilities when a user is served by a D2D helper, a small-cell base station (SBS) and a macro-cell base station (MBS). We formulate a delay minimization problem subject to the limited cache sizes of D2D helpers and SBSs. The structure of the optimal solutions to the problem is revealed, and then an improved standard gradient projection method is designed to effectively obtain the solutions. Both theoretical analysis and Monte-Carlo simulations validate the successful transmission probabilities. Compared with three benchmark caching policies, the proposed SVC-based random caching scheme is superior in terms of reducing the service delay.

Modeling multi-tier heterogeneous small cell networks: rate and coverage performance

The rapid growth of small cells is driving cellular network toward randomness and heterogeneity. The multi-tier heterogeneous network (HetNet) addresses the massive connectivity demands of the emerging cellular networks. Cellular networks are usually modeled by placing each tier (e.g macro, pico and relay nodes) deterministically on a grid which ignores the spatial randomness of the nodes. Several works were idealized for not capturing the interference which is a major performance bottleneck. Overcoming such limitation by realistic models is much appreciated. Multi-tier relay cellular network is studied in this paper, In particular, we consider {mathscr {K}}-tier transmission modeled by factorial moment and stochastic geometry and compare it with a single-tier, traditional grid model and multi-antenna ultra-dense network (UDN) model to obtain tractable rate coverage and coverage probability. The locations of the relays, base stations, and users nodes are modeled as a Poisson Point Process. The results showed that the proposed model outperforms the traditional multi-antenna UDN model and its accuracy is confirmed to be similar to the traditional grid model. The obtained results from the proposed and comparable models demonstrate the effectiveness and analytical tractability to study the HetNet performance.

An Energy-Efficient Framework for Internet of Things Underlaying Heterogeneous Small Cell Networks

Long-term evolution advanced (LTE-A) heterogeneous networks have been observed to offer reliable and service-differentiated communication, thereby enabling numerous mobile applications such as smart meters, remote sensors, and vehicular applications. This fact envisions the trend of Internet of Things (IoT) underlaying heterogeneous small cell networks. On this basis, this paper proposes an energy-efficient framework for such a scenario, where multitier heterogeneous small cell networks provide wireless connection and seamless coverage for mobile users and IoT nodes. In our proposed framework, an elastic cell-zooming algorithm based on the quality of service and traffic loads of end-users is performed by adaptively adjusting the transmission power of small cells in order to reduce energy consumption. In addition, aiming at the high energy efficiency of IoT underlaying small cell networks, a clustering-based IoT structure is used, where a SWIPT-CH selection algorithm is proposed to maximize the average residual energy of IoT nodes and to mitigate resource competition between IoT nodes and mobile users. Extensive simulations demonstrate that our proposed framework can significantly enhance the energy efficiency for IoT underlaying small cell networks with guaranteed outage probability.

Joint user association and resource allocation in HetNets based on user mobility prediction

Virtual small cell (VSC) formed by directional beams is seen as an alternative for the small base station (SBS) within the coverage of macro base station (MBS), to increase system capacity and reduce site cost. However, the flexibility of development for VSC poses challenges to user association and resource allocation in heterogeneous networks. In this paper, we consider the joint problem of user association and resource allocation in VSC aided multi-tier heterogeneous networks. To better analyze the formation of VSC and the impact of user mobility on the system, a user mobility prediction model is firstly constructed based on the Markov model. Then the joint user association and resource allocation problem is formulated to maximize the system capacity. Since the aforementioned problem is a coupling problem, two different solutions, namely, a decoupling solution and a coupling solution, are proposed based on the multi-agent Q-learning (MAQL) method, to find the optimal user association and resource allocation strategy. Moreover, to overcome the state and action space explosion in MAQL and accelerate convergence, the deep Q-network (DQN) is applied. Simulation results reveal that the deployment of VSC can increase the system capacity and spectrum efficiency. The coupling solution achieves better performance than the decoupling solution under a large number of users.

Analysis of the decoupled uplink downlink technique for varying path loss exponent in multi-tier HetNet

In this paper, the impact of varying path loss exponent (PLE) on user association probability, decoupled uplink coverage probability as well as decoupled uplink average spectral efficiency in downlink uplink decoupled (DUDe) multi-tier heterogeneous networks, is investigated. We investigate the effect of the difference in path loss exponents in both macro and small cell environments over uplink network performance. It is assumed that the mobile user connected to the macro base station experience different path loss exponent as compared to when connected to small base station. It is observed that the difference of path loss exponents in both cases has significant effect on the user association probability, decoupled uplink coverage probability as well as decoupled uplink average spectral efficiency. Moreover, in order to further support key findings and make sound comparison between coupled and DUDe performance in varying PLE environment, generalized analytical expressions for coupled association probabilities, along with coupled uplink coverage probability and coupled uplink average spectral efficiency have been derived. The analytical results evaluated in this paper are compared with the computer simulation and found in good agreement. Our analysis shows that decoupling technique performs suboptimal for cases where the environments around macro and small base stations are different with respect to each other. The work explained in this paper highlights the limitation of applying DUDe technique in realistic conditions where the PLEs of cellular tiers are not exactly equal to one another.

Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario

In 5G slice networks, the multi-tenant, multi-tier heterogeneous network will be critical in meeting the quality of service (QoS) requirement of the different slice use cases and in reduction of the capital expenditure (CAPEX) and operational expenditure (OPEX) of mobile network operators. Hence, 5G slice networks should be as flexible as possible to accommodate different network dynamics such as user location and distribution, different slice use case QoS requirements, cell load, intra-cluster interference, delay bound, packet loss probability, and service level agreement (SLA) of mobile virtual network operators (MVNO). Motivated by this condition, this paper addresses a latency-aware dynamic resource allocation problem for 5G slice networks in a multi-tenant, multi-tier heterogeneous environment, for efficient radio resource management. The latency-aware dynamic resource allocation problem is formulated as a maximum utility optimisation problem. The optimisation problem is transformed and the hierarchical decomposition technique is adopted to reduce the complexities in solving the optimisation problem. Furthermore, we propose a genetic algorithm (GA) intelligent latency-aware resource allocation scheme (GI-LARE). We compare GI-LARE with the static slicing (SS) resource allocation; the spatial branch and bound-based scheme; and, an optimal resource allocation algorithm (ORA) via Monte Carlo simulation. Our findings reveal that GI-LARE outperformed these other schemes.

Multi-UAV Assisted Multi-Tier Millimeter-Wave Cellular Networks for Hotspots With 2-Tier and 4-Tier Network Association

The evolution of the fifth-generation (5G)/ beyond 5G (B5G) mobile communication networks greatly depends on the seamless integration of terrestrial and sky networks over advanced multi-tier heterogeneous network (HetNet) infrastructure. By using the huge potential of unmanned aerial vehicles (UAVs) and mm-Wave, we develop a novel and practical multi-UAV assisted multi-tier HetNet model which consists of clustered aerial UAV base stations (U-BSs) and Poisson point process (PPP) based ground BSs (G-BSs) for emergency and crowded hotspot area. In a typical cluster, both ground user equipments (GUEs) and UAVs are modeled as Poisson cluster process (PCP) and scattered around the common cluster center. Specially, the analysis is conducted by adding two additional tiers which consist of multiple intra-cluster U-BSs and single G-BS in representative cluster so that the point sets of U-BSs and G-BSs are partitioned into two sub-sets, respectively, and a 4-tier network model is formed. To find the contribution of the inter-cluster associations on the performance of networks, we construct 2-tier and 4-tier association schemes. The 2-tier association allows a GUE associated only with intra-cluster U-BSs and G-BS, while the 4-tier association allows all inter/intra-cluster U-BSs and G-BSs can be associated. Then, according to stochastic geometry methods, statistical description of the downlink interferences experienced at a typical GUE is derived. This derivation yields the downlink coverage probabilities and total network throughput are obtained. It is achieved that association probabilities greatly depend on the distribution of daughter point process. UAVs' height and the distributions of U-BSs and GUEs impose non-monotonous impact on coverage probabilities. Due to severe inter-cluster interference, the achievable average area throughput is not always increasing with SINR so that there is an optimal SINR threshold. In addition, our analysis finds the proposed 4-tier association scheme outperforms the simple 2-tier one in terms of the average area throughput.

Full-Duplex Two-Tier Heterogeneous Network With Decoupled Access: Cell Association, Coverage, and Spectral Efficiency Analysis

The ever increasing thirst for the higher capacity demands radical changes in the design of cellular networks, such as a leap from single-tier homogeneous networks to multi-tier heterogeneous networks and the use of millimeter wave frequency band. A typical point-to-point full-duplex transmission link can double the link rate by simultaneously using the same spectrum for bidirectional traffic. However, the characterization of full-duplex two-tier heterogeneous networks is not as straightforward as that of point-to-point full-duplex systems, specially when the different tiers of the heterogeneous network use different frequency bands (millimeter wave and microwave) for their transmissions. This paper characterizes a full-duplex two-tier heterogeneous network with decoupled access, where both tiers operate on different frequency bands (millimeter wave and microwave). To evaluate the achievable spectral efficiency and association behavior of users and base stations, a two-tier heterogeneous network model is proposed in which all users and base stations are modeled using Poisson point processes. First a signal-to-interference-plus-noise-ratio optimal user association scheme is characterized. Based on the user association scheme, the spectral efficiencies of the uplink and downlink transmission links are derived. In addition, a thorough analysis of the signal-to-interference-plus-noise-ratio coverage is also provided. Moreover to render the analytical model more comprehensive and robust, i.e., different from the convention of noise-limited millimeter wave network, the interference in millimeter wave networks is also accounted for in the analytical model. Lastly, the pragmatic value of full-duplex heterogeneous networks and decoupled access is discussed in detail through numerous numerical and simulation results.

Flexible pilot allocation scheme for massive MIMO two‐tier heterogeneous networks

Existing research demonstrates that pilot contamination is one major factor that restricts the system performance of time division duplex massive multiple-input multiple-output (MIMO) systems. Reasonable pilot allocation is an effective method to reduce pilot contamination. However, most existing pilot allocation methods (whether for one-tier or multi-tier networks) focus on cells with the same size, or regular shape, or fixed number of users per cell, so they are inflexible and not applicable to massive MIMO multi-tier heterogeneous networks (HetNets) with irregular shaped cells and random distributed users. To solve this problem, this study introduces the idea of coalition game into pilot allocation and proposes a pilot allocation scheme based on coalition game. The utility function of each user for coalition game is analysed; the adjustment principle of the coalition structure and the coalition formation algorithm are given. Simulations results show that the proposed scheme can be flexibly used in many massive MIMO scene that base stations and users are randomly distributed (such as one-tier networks, multi-tier HetNets, ultra-dense HetNets, etc.), and it can effectively reduce pilot contamination and improve the received signal to interference plus noise ratio (SINR) and spectral efficiency (SE) of the uplink.

Multitier heterogeneous network using stochastic geometry and factorial moment approaches

SummaryThe rapid growth of small cells is driving cellular network toward randomness and heterogeneity. Usually, cellular networks are modeled by placing each tier (eg, macro, pico, and relay nodes) deterministically on a grid. In such a heterogeneous cellular network, the rational approach to characterize the base stations (BSs), user, and relay locations is by using random spatial models. When calculating the metric performances such as coverage probability, these networks are idealized without consideration of interference. Therefore, interference modeling remains the key issue for the deployment of small cells. This paper developed a single and multitier cellular network model that captures the downlink heterogeneous cellular network with variable parameters such as the target signal‐to‐interference ratio (SIR), transmitted power, and deployment density. In particular, we model ‐tier transmission and compare it with a single‐tier and traditional grid model to obtain tractable coverage probability using stochastic geometry and factorial moment. The obtained results demonstrate the effectiveness and analytical tractability to study the heterogeneous performance.

Rate and coverage analysis in multi-tier heterogeneous network using stochastic geometry approach

To meet massive wireless traffic demand in the upcoming fifth generation cellular networks, the rapid growth of small cells is emerging as an attractive solution and deriving cellular network toward randomness and heterogeneity. In a typical macrocell, there are many deployed femtocells and few picocells with unplanned users. In such a heterogeneous cellular network, using random spatial models is a rational approach to characterize the base stations (BS) locations. The key issue for the deployment of small cells is interference management. Considering multi-tier cellular network, in this paper we develop a general kth-tier BSs model that captures the downlink multi-antenna heterogeneous cellular network with variable parameters such as the number of antenna, target signal-to-noise-and-interference ratio (SINR), transmitted power, and deployment density. In particular, we consider K−tier transmission and compare it with a single-tier, traditional grid model and multi-antenna ultra-dense network (UDN) model to obtain tractable rate and coverage probability. The results showed that the proposed model outperforms the traditional multi-antenna ultra-dense network (UDN) model and its accuracy is confirmed to be similar to the traditional grid model. In addition, a comparison with the counterpart uplink model is provided, which reveals that the coverage probability of the proposed downlink model decreases when the fractional power control (ϵ) increases in the uplink.

Effective User-Pair Association Schemes for Relay-Based Multi-tier Heterogeneous Networks with Physical Layer Security

This paper focuses on relay-assisted multi-tier heterogeneous networks (HetNets) in term of feasible user-pair association (UPA) criterions and physical layer secrecy analysis. In the interesting relay-assisted multi-tier HetNets, the randomly located mobile user-pair communicates with the help of the relay of its associated tier. We model the locations of all network elements as independent Poisson point process. For such relay-assisted HetNets, similar to the nearest relay defined for user association in traditional single-hop HetNets, we define the so-called best relay in each tier for a typical mobile user-pair by using the equivalent end-to-end biased received power (BRP). Then based on the defined best-relay, we first propose the max–min user-pair association (MM-UPA) criterion. Due to the fact that the MM-UPA criterion is dominated by the bottleneck link’s BRP and does not exploit the joint effect of both the source-relay and relay-destination links, we present the maximum harmonic mean user-pair association (MHM-UPA) criterion, again. For the two UPA criterions, by using feasible mathematical analysis, we derive the corresponding UPA probabilities. Finally, as an implement of the two proposed UPA criterions, by using stochastic geometry, we perform the secrecy performance analysis of the considered relay-assisted multi-tier HetNets. The presented numerical analysis first validates our derivations through the comparison analysis with traditional single-hop user association criterion. At the same time, we also present the comparison analysis between the two proposed MM-UPA and MHM-UPA criterions. It is found that when the transmission power $$P_{R(S)}^{k}$$ is small, the MHM-UPA scheme outperforms the MM-UPA one in term of UPA probability. On the contrary, the two schemes achieve approximately the same UPA probability. For the total secrecy probability, we find that when transmit power is small, the MHM-UPA achieves the higher secrecy probabilities. Moreover, the achieved gain by MHM-UPA is increasing with the decrease of transmission power. Contrarily, when the transmission power is large, although the MM-UPA outperforms the MHM-UPA, the achieved gain by MM-UPA cover MHM-UPA is small.

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.

Energy Efficient Traffic Offloading in Multi-Tier Heterogeneous 5G Networks Using Intuitive Online Reinforcement Learning

The energy efficiency in multi-tier heterogeneous 5G networks is a critical issue due to the fact that the macro base stations (BSs) power consumption is considerably high and proportional to their traffic load. Traffic offloading from macrocells to small cells is envisioned as a potential solution to improve energy efficiency in 5G heterogeneous networks. However, traffic offloading causes traffic congestion at small cells, interference as a result of small cells transmissions, and aggregate power consumption of small cells. These factors make the traffic offloading procedure more challenging. In this paper, we propose a conditional traffic offloading scheme, which relies on macrocells and small cells system load information to determine the most energy efficient traffic offloading strategy, select the proper operation mode of small cells, and fulfill macro users applications' quality of service (QoS) requirements. The proposed scheme is developed using a novel intuitive online reinforcement learning methodology to perform the conditional traffic offloading in which each macro BS conjectures the offloading strategies of other macrocells. The convergence of the proposed scheme is proved and numerical results demonstrate its capability to achieve fast convergence with QoS guarantee and significant energy efficiency.

An optimal multitier resource allocation of cloud RAN in 5G using machine learning

AbstractThe networks are evolving drastically since last few years in order to meet user requirements. For example, the 5G is offering most of the available spectrum under one umbrella. In this work, we will address the resource allocation problem in fifth‐generation (5G) networks, to be exact in the Cloud Radio Access Networks (C‐RANs). The radio access network mechanisms involve multiple network topologies that are isolated based on the spectrum bands and it should be enhanced with numerous access technology in the deployment of 5G network. The C‐RAN is one of the optimal technique to combine all the available spectral bands. However, existing C‐RAN mechanisms lacks the intelligence perspective on choosing the spectral bands. Thus, C‐RAN mechanism requires an advanced tool to identify network topology to allocate the network resources for substantial traffic volumes. Therefore, there is a need to propose a framework that handles spectral resources based on user requirements and network behavior. In this work, we introduced a new C‐RAN architecture modified as multitier Heterogeneous Cloud Radio Access Networks in a 5G environment. This architecture handles spectral resources efficiently. Based on the simulation analysis, the proposed multitier H‐CRAN architecture with improved control unit in network management perspective enables augmented granularity, end‐to‐end optimization, and guaranteed quality of service by 15 percentages over the existing system.

Energy Efficient and Delay Aware 5G Multi-Tier Network

Multi-tier heterogeneous Networks (HetNets) with dense deployment of small cells in 5G networks are expected to effectively meet the ever increasing data traffic demands and offer improved coverage in indoor environments. However, HetNets are raising major concerns to mobile network operators such as complex distributed control plane management, handover management issue, increases latency and increased energy expenditures. Sleep mode implementation in multi-tier 5G networks has proven to be a very good approach for reducing energy expenditures. In this paper, a Markov Decision Process (MDP)-based algorithm is proposed to switch between three different power consumption modes of a base station (BS) for improving the energy efficiency and reducing latency in 5G networks. The MDP-based approach intelligently switches between the states of the BS based on the offered traffic while maintaining a prescribed minimum channel rate per user. Simulation results show that the proposed MDP algorithm together with the three-state BSs results in a significant gain in terms of energy efficiency and latency.