Heterogeneous Cellular Networks Research Articles

Energy-efficient association mechanism designed for uplink CDMA-based HCNs

ABSTRACTTo reduce the energy consumption and prolong the battery lifetimes of mobile terminals, the design of energy-efficient association scheme is necessary and meaningful. To this end, we design a type of association mechanism (scheme) to maximize the whole energy efficiency (WEE) for uplink code-division-multiple-access (CDMA)-based heterogeneous cellular networks (HCNs), and formulate it as a WEE maximization problem with users’ SINR (signal-to-interference-plus-noise ratio) constraints. Considering that the finally formulated problem is in a fractional mixed-integer form and hard to tackle, we introduce an energy efficiency (EE) parameter to convert it into a parametric subtractive form. At last, we design two two-layer iterative algorithms for the formulated problem, whose primary difference lies in the treatment of SINR constraints. In general, the outer loop utilizes a bisection method to search the optimal EE parameter, and the inner loop alternately optimizes the association index and transmit power. At last, we give the corresponding convergence analyses for some subalgorithms, and also give some detailed complexity analyses for the whole algorithm. In the simulation, we introduce an existing energy-efficient association mechanism for comparison, and finally investigate the impacts of different network parameters on the association performance.

Device-Aware Cell Association in Heterogeneous Cellular Networks: A Matching Game Approach

Heterogeneous cellular networks (HCNs) provide a promising paradigm for supporting different types of devices that have diverse quality of service (QoS) requirements, such as Internet of Things devices (IoTDs) and human-to-human devices (H2HDs). In this paper, a distributed cell association algorithm is developed to consider the dissimilar association requirements for IoTDs and H2HDs coexisting in HCNs. The device association process is formulated as a multi-objective optimization problem to minimize the uplink (UL) transmit power for IoTDs and maximize the downlink (DL) data rate for H2HDs while considering the various devices’ QoS requirements. To solve this problem, an approach dependent on matching theory is proposed to model the interactions between devices and base stations in the network. Using this approach, a distributed algorithm is developed to provide the device association solution. The proposed algorithm is then proved to converge to a stable matching. Simulation results validate the effectiveness of the proposed algorithm in improving the UL power performance for IoTDs as well as DL rate performance for H2HDs compared to other association algorithms.

Device-to-Device Communications Enabled Multicast Scheduling for mmWave Small Cells Using Multi-Level Codebooks

Heterogeneous cellular networks with small cells in the millimeter wave (mmWave) band densely deployed have become one of promising candidates for future wireless networks due to huge bandwidth available in the mmWave band. To overcome high path loss in the mmWave band, the beamforming technique of directional antennas is adopted. Consequently, concurrent transmissions of links can be enabled to improve network capacity. On the other hand, multicast services can support many applications like popular content downloading and broadcast communication services. In user intensive region where multicast services usually happen, device-to-device (D2D) communications in physical proximity provide better channel conditions, and can improve multicast efficiency. In this paper, we develop an efficient multicast scheduling scheme for mmWave small cells, referred to as CONMD2D, where both concurrent transmissions and D2D communications are exploited based on a multi-level antenna codebook to optimize network performance. In CONMD2D, the multicast group is partitioned into subgroups, and D2D transmission paths are established between subgroups. Then, a concurrent scheduling algorithm schedules the multicast links concurrently into the transmission stage. Performance evaluation under various system parameters demonstrates CONMD2D achieves significant improvement in network throughput and energy efficiency compared with other state-of-the-art schemes.

Interference Precancellation for Resource Management in Heterogeneous Cellular Networks

Network densification by installing more cellular stations (cells) with smaller coverage is promising to improve wireless capacity to meet the explosive growth of cellular traffic. The macrocellular base station and smaller cells with different coverage form heterogeneous cellular networks. Typically, the smaller cells operate in the same spectrum as the macrocells. Most of the existing interference mitigation approaches either rely on resource isolation or power auto-configuration. In cellular networks, the data to all cells and the mobile stations (MSs) are originated from the core cellular network. We take advantage of this characteristic and propose a technique called interference precancellation . If the exact interferer to an MS is identified, the victim cell that serves the victim MS transmits the interference precanceled signal, which is the signal intended for the victim MS subtracts the interference signal. The interference precanceled signal and the interference signal scramble at the victim MS and became the intended signal. With interference precancellation, the interferer and the victim cell can utilize the same set of resources and thus the capacity is further improved. However, some MSs are interference-free, and for MSs whose exact interferers cannot be determined, the MSs still require resource isolation. Therefore, we propose an algorithm for resource management with interference precancellation (RMIP) that jointly considers MSs experiencing a different level of interference. Through experiments on GNU Radio/USRP, we show that the known interference signal can be precanceled and the combination of the interference signal and the precanceled signal becomes the intended signal. Simulation results show that if all exact interferers are identified, RMIP algorithm achieves higher throughput compared with pure resource isolation.

Energy-Aware Resource Management in Heterogeneous Cellular Networks With Hybrid Energy Sources

In this paper, we focus on reducing the on-grid energy consumption in heterogeneous radio access networks (HetNets) supplied with hybrid power sources (grid and renewables). The energy efficiency problem is analyzed over both short- and long-timescales by means of reactive and proactive management strategies. For short-timescale case, a renewable-energy (RE) aware user equipment-base station association is proposed and analyzed for the cases when no storage infrastructure is available. For long-timescale case, a traffic flow method is proposed for load balancing in RE base stations (BSs), which is combined with a model predictive controller (MPC) to include forecast capabilities of the RE source behavior in order to better exploit a Green HetNet with storage support. The mechanisms are evaluated with data of solar measurements from the region of Valle de Aburra, Medellin, Colombia and wind estimations from the Moscow region, Russian Federation. Results show how the green association proposal can reduce on-grid energy consumption in a HetNet by up to 34%, while is able to exceed the savings obtained by other methods, including the best-signal level policy by up to 15%, additionally providing high network efficiency and low computational complexity. For the long-timescale case, MPC attainable savings can be up to 22% with respect to the on-grid only Macro-BS approach. Finally, an analysis of our proposals in a common scenario is included, which highlights the relevance of storage management, although emphasizing the importance of combining reactive and proactive methods in a common framework to exploit the best of each approach.

Coverage analysis of ultra-dense heterogeneous cellular networks with interference management

Deploying ultra-dense small base stations (SBSs) in the coverage umbrella of a macro base station (MBS) requires proactive users offloading form MBS to SBSs to achieve maximum performance gain in heterogeneous cellular networks. However, it degrades the signal-to-interference-plus-noise ratio (SINR) of the offloaded users due to strong interference received from MBS. To improve users’ SINR, an efficient interference mitigation scheme is required to be used in conjunction with users offloading. Soft frequency reuse (SFR) is an attractive and spectrally efficient interference mitigation scheme that allocates available bandwidth among all cell users associated with $$k{\text{BS}}$$, where $$k\in ({\text{M}},{\text{S}})$$. To address the problem of interference, we use the SFR scheme together with power control factor $$(\beta )$$ to transmit at different power levels for interior and edge regions of $$k{\text{BS}}$$, i.e., $$r^i_{k} \,{\text{and}}\, r^e_{k}$$, respectively. We further consider uniform and nonuniform SBS distribution in the premises of MBS and analyse the effect of the SFR scheme on the proposed model with the help of Stochastic geometry. Mathematical expressions for coverage probabilities are derived and validated through simulations. Numerical results show that the proposed model achieves better coverage probability due to reduced interference. Moreover, nonuniform SBS distribution together with the SFR scheme further improves the performance gain of the proposed model.

Optimal radio resource allocation to achieve a low BER in PD‐NOMA–based heterogeneous cellular networks

AbstractIn this paper, the problem of downlink radio resource allocation for a power‐domain nonorthogonal multiple‐access–based heterogeneous cellular network is investigated. We propose two scenarios: (1) resource allocation with exclusive subcarrier allocation and (2) resource allocation considering intercell interference. The aim of this paper is to obtain joint subcarrier and power allocation for the two considered system models by addressing the maximization of the users' sum rate subject to the bit error rate constraint, the successive interference cancellation constraint, subcarrier constraints, and the transmit power restriction of each base station. To solve the corresponding optimization problems, an alternating method is applied by decoupling the proposed problems into two subproblems, namely, subcarrier allocation problem and power allocation problem, where they are solved by using the mesh adaptive direct search algorithm and different successive convex approximation methods, respectively. Moreover, to evaluate the optimality gap of the alternating method, the proposed problems are solved using an optimal method, namely, monotonic optimization with high complexity as a benchmark. As the results show, with the bit error rate constraint, the link‐level performance, at the cost of a decreasing system sum rate, is improved.

Coverage-Rate Tradeoff Analysis in mmWave Heterogeneous Cellular Networks

In this paper, we first introduce a generalized modeling and analysis framework to explore the fundamental interactions between user association, coverage probability, and link rate in a millimeter-wave (mmWave) heterogeneous cellular network (HetNet), in which there are multiple tiers of the ultra-high-frequency (UHF) macrocell and small-cell base stations (BSs) and a single tier of mmWave small-cell BSs. A generalized user association scheme that can cover many path-loss-based user association schemes is proposed, and its related probabilistic properties that facilitate the derivations of the coverage probability and link rate are derived. The derived general expressions of the coverage and link rate not only shed light on how to design user association functions in order to maximize the coverage and link rate but also show that it is impossible to devise a user association scheme that maximizes the coverage and link rate at the same time. Namely, there exists a fundamental tradeoff between the coverage and link rate in mmWave HetNets with distinct bandwidths in the UHF and mmWave bands while a user is my margin associating with a BS. We characterize the coverage-optimal and rate-optimal user association schemes and numerically validate their performances and show the coverage-rate tradeoff problem.

Downlink Coverage Probability in Cellular Networks With Poisson–Poisson Cluster Deployed Base Stations

Poisson-Poisson cluster processes (PPCPs) are a class of point processes exhibiting attractive point patterns. Recently, PPCPs are actively studied for modeling and analysis of heterogeneous cellular networks or device-to-device networks. However, surprisingly, to the best knowledge of the author, there is no exact derivation of downlink coverage probability in a numerically computable form for a cellular network with base stations (BSs) deployed according to a PPCP within the most fundamental setup such as single-tier, Rayleigh fading and nearest BS association. In this paper, we consider this fundamental model and derive a numerically computable form of coverage probability. To validate the analysis, we compare the results of numerical computations with those by Monte Carlo simulations and confirm the good agreement.

Multi‐objective optimisation for heterogeneous cellular network planning

Small cell aims at improving the cell coverage and capacity of macrocell. Network operators investigate cell planning for improving system performance and for satisfying user requirements with minimal construction cost and least unserved users. Most of the existing literature merely considered a single objective function or investigated cell planning for small-scale and homogeneous networks. This study aims to optimise multiple objective functions of a large-scale and heterogeneous wireless network with multiple macrocells and multiple small cells. The authors formulate the multi-objective optimisation problem of cell planning for heterogeneous cellular networks. The three objects include construction cost, number of unserved users and network capacity. Then they propose the large-scale cell planning genetic algorithm (LSCPGA) to find a planning result with the lowest fitness value. Simulation results show that LSCPGA economises 9-20% construction cost, eliminates the number of unserved users from 4 to 10% and enhances 2-15% in network capacity compared to other planning algorithms.

CoMP Transmission for Safeguarding Dense Heterogeneous Networks with Imperfect CSI

To ensure reliable and secure communication in heterogeneous cellular network (HCN) with imperfect channel state information (CSI), we proposed a coordinated multipoint (CoMP) transmission scheme based on dual-threshold optimization, in which only base stations (BSs) with good channel conditions are selected for transmission. First, we present a candidate BSs formation policy to increase access efficiency, which provides a candidate region of serving BSs. Then, we design a CoMP networking strategy to select serving BSs from the set of candidate BSs, which degrades the influence of channel estimation errors and guarantees qualities of communication links. Finally, we analyze the performance of the proposed scheme, and present a dual-threshold optimization model to further support the performance. Numerical results are presented to verify our theoretical analysis, which draw a conclusion that the CoMP transmission scheme can ensure reliable and secure communication in dense HCNs with imperfect CSI.

Corrections to “Secrecy Outage Analysis for Distributed Antenna Systems in Heterogeneous Cellular Networks”

In [1] , the calculation of (8) was erroneous. To be specific, as shown in (8) of [1] , the average transmit power of a specially-designed signal ${x_{m} = - {{\sqrt {P_{S}} {h_{Sm}}h_{Am}^{*}{x_{S}}}}/{{{{\left |{ {{h_{Am}}} }\right |}^{2}}}}}$ was obtained as \begin{equation*}{P_{m} = \frac {{\sigma _{Sm}^{2}}}{{\sigma _{Am}^{2}}}}P_{S},\end{equation*} where $\sigma _{Sm}^{2} = E(|{h_{Sm}}{|^{2}})$ and $\sigma _{Am}^{2} = E(|{h_{Am}}{|^{2}})$ . This calculation was obtained by mistaking an expectation of $1/|h_{Am}|^{2}$ for $E(1/|h_{Am}|^{2})=1/E(|h_{Am}|^{2})= 1/\sigma _{Am}^{2}$ , which is erroneous to be corrected. Actually, considering that $|h_{Am}|^{2}$ is an exponentially distributed random variable with a mean of $\sigma ^{2}_{Am}$ , the expectation of $1/|h_{Am}|^{2}$ tends toward infinity, rather than $1/\sigma _{Am}^{2}$ .

Single or Multiple Frames Content Delivery for Next-Generation Networks?

This paper addresses the four enabling technologies, namely multi-user sparse code multiple access (SCMA), content caching, energy harvesting, and physical layer security for proposing an energy and spectral efficient resource allocation algorithm for the access and backhaul links in heterogeneous cellular networks. Although each of the above mentioned issues could be a topic of research, in a real situation, we would face a complicated scenario where they should be considered jointly, and hence, our target is to consider these technologies jointly in a unified framework. Moreover, we propose two novel content delivery scenarios: 1) single frame content delivery (SFCD), and 2) multiple frames content delivery (MFCD), where the time duration of serving user requests is divided into several frames. In the first scenario, the requested content by each user is served over one frame. However, in the second scenario, the requested content by each user can be delivered over several frames. We formulate the resource allocation for the proposed scenarios as optimization problems where our main aim is to maximize the energy efficiency of access links subject to the transmit power and rate constraints of access and backhaul links, caching and energy harvesting constraints, and SCMA codebook allocation limitations. Due to the practical limitations, we assume that the channel state information values between eavesdroppers and base stations are uncertain and design the network for the worst case scenario. Since the corresponding optimization problems are mixed integer non-linear and nonconvex programming, NP-hard, and intractable, we propose an iterative algorithm based on the well-known alternate and successive convex approximation methods. In addition, the proposed algorithms are studied from the computational complexity, convergence, and performance perspectives. Moreover, the proposed caching scheme outperforms the existing traditional caching schemes like random caching and most popular caching. We also study the effect of joint and disjoint considerations of enabling technologies for the performance of next-generation networks. On the one hand, our proposed caching strategy increases slightly the computational complexity by 3%, 1.1%, and 2% compared to no caching, SFCD, and disjoint solution, respectively. On the other hand, the proposed caching scheme achieves a performance gain of 43%, 9.4%, and 51.3% compared to the three state-of-the-art schemes.

SIR Meta Distribution for Spatiotemporal Cooperation in Poisson Cellular Networks

The meta-distribution provides more fine-grained information on the signal-to-interference ratio (SIR) compared to the SIR distribution at the typical user. This paper studies the SIR meta-distribution in heterogeneous cellular networks (HCNs) for JT-DPB with two types of hybrid automatic repeat request (HARQ) techniques, where JT-DPB is a general scheme for base station cooperation that combines joint transmission (JT) and dynamic point blanking (DPB). This paper also considers two types of typical users—the general user and the worst-case user (the typical user located at the Voronoi vertex in a single-tier network). For the Type-II HARQ, a simplified network model is proposed, which leads to a tractable and accurate approach for the SIR meta-distribution analysis. The analytical results for the Type-I HARQ and Type-II HARQ are presented.

Joint Cache Partitioning, Content Placement, and User Association for D2D-Enabled Heterogeneous Cellular Networks

The rapid growth of traffic demands has posed the challenges to both radio access networks (RANs) and backhaul links. While the device-to-device (D2D)-enabled heterogeneous cellular networks (HCNs) are expected to offer diverse radio access capabilities and to improve the transmission performance of user equipments (UEs) significantly, the backhaul links may still experience challenges in offering quality-of-service guaranteed services to UEs. To tackle these problems, caching technology, i.e., caching user contents at the infrastructures of RANs, is proposed as an effective approach. In this paper, we consider the joint cache partitioning, content placement, and user association problem in the D2D-enabled HCNs and propose a two-step algorithm. Aiming to improve the utilization of cache space at small base stations, we propose a bankruptcy game-based cache partitioning algorithm to obtain the optimal cache space allocation strategy, based on which we then propose a joint content placement and user association algorithm to achieve the minimum service delay of all the content request users. As the formulated optimization problem is a mixed integer nonlinear optimization problem which cannot be solved conveniently, we apply the McCormick envelopes and the Lagrangian partial relaxation method to decompose the optimization problem into three subproblems which can be iteratively solved by means of the modified Kuhn–Munkres algorithm and the unidimensional knapsack algorithm. Simulation results validate the effectiveness of our proposed scheme.

Fundamentals of Simultaneous Wireless Information and Power Transmission in Heterogeneous Networks: A Cell-Load Perspective

In a heterogeneous cellular network (HetNet) consisting of multiple different types (tiers) of base stations (BSs), the void cell event in which a BS does not have any users has been shown to exist due to user-centric BS association and its probability is dominated by the cell load of each tier. Such a void cell phenomenon has not been well characterized in the modeling and analytical framework of simultaneous wireless information and power transmission (SWIPT) in a HetNet. This paper aims to accurately exploit the fundamental performance limits of the SWIPT between a BS and its user by modeling the cell-load impact on the downlink and uplink transmissions of each BS. We first characterize the power-splitting receiver architecture at a user and analyze the statistical properties and limits of its harvested power and energy, which reveals how much of the average energy can be harvested by users and how likely the self-powered sustainability of users can be achieved. We then derive the downlink and uplink rates that characterize the cell-load and user association effects and use them to define the energy efficiency of a user. The optimality of the energy efficiency is investigated, which maximizes the SWIPT performance of the receiver architecture for different user association and network deployment scenarios.

TARCO: Two-Stage Auction for D2D Relay Aided Computation Resource Allocation in HetNet

In heterogeneous cellular network, task scheduling for computation offloading is one of the biggest challenges. Most works focus on alleviating heavy burden of macro base stations by moving the computation tasks on macro-cell user equipment (MUE) to remote cloud or small-cell base stations. But the selfishness of network users is seldom considered. Motivated by the cloud edge computing, this paper provides incentive for task transfer from macro cell users to small cell base stations. The proposed incentive scheme utilizes small cell user equipment to provide relay service. The problem of computation offloading is modelled as a two-stage auction, in which the remote MUEs with common social character can form a group and then buy the computation resource of small-cell base stations with the relay of small cell user equipment. A two-stage auction scheme named TARCO is contributed to maximize utilities for both sellers and buyers in the network. The truthful, individual rationality and budget balance of the TARCO are also proved in this paper. In addition, two algorithms are proposed to further refine TARCO on the social welfare of the network. Extensive simulation results demonstrate that, TARCO is better than random algorithm by about 104.90% in terms of average utility of MUEs, while the performance of TARCO is further improved up to 28.75% and 17.06% by the proposed two algorithms, respectively.

Energy-Efficient Deployment and Adaptive Sleeping in Heterogeneous Cellular Networks

This paper focuses on energy efficiency that is a key performance metric in heterogeneous cellular networks to two key areas. First, based on the Poisson point process distributions of small-cell base stations (SBSs) and macrocell base stations (MBSs), the energy-efficiency model is formulated, and the effect of base stations’ distribution on energy efficiency is analyzed. For maximizing energy efficiency, the joint optimal densities of SBSs and MBSs are deduced under the constraint of quality of service. Second, according to this, we propose a joint sleep strategy of MBSs and that of SBSs. We deduce the optimal threshold of traffic load according to the joint optimal densities. If the traffic load of SBSs (or MBSs) is less than the optimal threshold of traffic load, these SBSs (or MBSs) go to sleep; otherwise, it is activated. This makes the SBSs and MBSs adaptively and distributively sleep according to their own traffic loads. The simulation results verify that the deduced joint optimal densities of the SBS and the MBS are accurate, and energy efficiency is improved when SBSs and MBSs adaptively sleep.

Channel Access and Power Control for Energy-Efficient Delay-Aware Heterogeneous Cellular Networks for Smart Grid Communications Using Deep Reinforcement Learning

Cellular technology with long-term evolution (LTE)-based standards is a preferable choice for smart grid neighborhood area networks due to its high availability and scalability. However, the integration of cellular networks and smart grid communications puts forth a significant challenge due to the simultaneous transmission of real-time smart grid data which could cause radio access network (RAN) congestions. Heterogeneous cellular networks (HetNets) have been proposed to improve the performance of LTE because HetNets can alleviate RAN congestions by off-loading access attempts from a macrocell to small cells. In this paper, we study energy efficiency and delay problems in HetNets for transmitting smart grid data with different delay requirements. We propose a distributed channel access and power control scheme, and develop a learning-based approach for the phasor measurement units (PMUs) to transmit data successfully by considering interference and signal-to-interference-plus-noise ratio (SINR) constraints. In particular, we exploit a deep reinforcement learning(DRL)-based method to train the PMUs to learn an optimal policy that maximizes the earned reward of successful transmissions without having knowledge on the system dynamics. Results show that the DRL approach obtains good performance without knowing the system dynamic beforehand and outperforms the Gittin index policy in different normal ratios, minimum SINR requirements and number of users in the cell.

Analysis of Downlink Uplink Decoupled Dense Heterogeneous Cellular Network based on User Association using Multi-Slope Path Loss Model

Keeping in consideration the expected need of node densification of heterogeneous cellular networks in near future, it is imperative that more accurate path loss models be used when an ...