Scheme For Heterogeneous Networks Research Articles

Efficient and Privacy-Preserving Cloud-Assisted Two-Party Computation Scheme in Heterogeneous Networks

Efficient and Privacy-Preserving Cloud-Assisted Two-Party Computation Scheme in Heterogeneous Networks

Minimizing outage probability driven wireless backhaul scheme in heterogeneous networks

Heterogeneous networks (HetNets) attracts a lot of attention due to its high capacity and large coverage for future communication networks. However, with the large-scale deployment of small cells, HetNets bears dramatically increasing backhaul, which leads to a decrease of the outage performance. To improve the outage performance of HetNets, we propose a wireless backhaul scheme for a two-layer HetNets, which automatically switches the three basic modes of orthogonal multiple access (OMA), nonorthogonal multiple access (NOMA) and cooperative non-orthogonal multiple access (CNOMA). First, we analyze the backhaul capacity and outage performance of these three basic modes. Then, we design the power allocation schemes based on minimizing outage probability for NOMA and CNOMA. Using the designed power allocation schemes, we propose a wireless backhaul scheme that switches the three modes according to the channel quality among different base stations (BSs). Moreover, the closed-form of the corresponding outage probability is derived. Compared with the three basic modes, the proposed wireless backhaul scheme can achieve the best outage performance and a higher backhaul capacity. Finally, all the analytical results are validated by simulations.

Joint Interference Alignment and Power Control for Dense Networks via Deep Reinforcement Learning

This letter proposes a joint interference suppression scheme in heterogeneous networks (HetNets) with dense small cells (SCs) and users. Different from the majority of existing studies, we adopt the co-tier intra-cell interference alignment (IA), while the co-tier inter-cell and cross-tier interference is suppressed by centralized power control in the macro base station (MBS). Specifically, the power control problem is modeled as a Markov Decision Process (MDP) with the aim of maximizing the sum spectrum efficiency. Considering the exponential growth of the output layer neurons faced by general deep reinforcement learning (DRL) algorithms, we propose a deep deterministic policy gradient (DDPG)-based algorithm to solve the problem. Simulation results demonstrate that the proposed algorithm is able to achieve better performance and wider application scope comparing with existing 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.

Analysis and design of an efficient handoff management strategy via velocity estimation in HetNets

AbstractIn this paper, we present an efficient handoff decision strategy and a mobility state detection (MSD) scheme for heterogeneous networks (HetNets). Due to base station (BS) densification, HetNets occasionally face unnecessary handovers and service failures. Since velocity plays a crucial role in handover process, its knowledge is imperative for effective mobility management. Furthermore, due to limited power in mobile devices, emphasis is in investigation of velocity estimators that are at service provider end. Thus, we propose two maximum likelihood–based velocity estimators exploiting handover count and sojourn time measurements, respectively. Our analysis illustrates that both the estimators are asymptotically unbiased and efficient. In addition, we also notice that variance of sojourn time–based estimator is smaller than that of handover count–based estimator. Considering superiority of sojourn time–based estimator, we propose a handover decision strategy to minimize unnecessary handovers. Here, we first predict the sojourn time of upcoming BSs on the basis of velocity estimated via sojourn time samples. Next, BSs whose predicted sojourn time are greater than a prespecified threshold are then considered to identify the next serving BS. Finally, we select next serving BS on the basis of minimum cost for satisfying quality‐of‐service parameters such as bandwidth, security, monetary cost, and available power at user device. This work also exploits estimated velocity to investigate MSD specified in LTE standards. The numerical and simulation results validate our approach by illustrating accuracy in velocity estimation, reduction in frequent handovers and service failures, and improvement in MSD.

Green Cooperative Sensing Scheme in Heterogeneous Networks

Cognitive radio technology is still the key technology of future mobile communication systems. Previous studies have focused on improving spectrum utilization and less energy consumption. In this paper, we propose an Overhead Reduced Scheme (ORS) for green cooperative spectrum sensing. Compared to traditional cooperative sensing scheme, ORS scheme divides the sensing time into three time slots and selects the best multi-mode user to report decisions. In consideration of reporting channel deviation, we derive closed-form expressions for detection probability and false alarm probability of ORS scheme based on Rayleigh fading channel. Simulation results show that ORS scheme can improve the perception accuracy while reducing the perceived delay and energy consumption in the process of perception, so as to realize the green communication.

Joint Computation Offloading and Resource Allocation Optimization in Heterogeneous Networks With Mobile Edge Computing

In this paper, we propose a distributed joint computation offloading and resource allocation optimization (JCORAO) scheme in heterogeneous networks with mobile edge computing. An optimization problem is formulated to provide the optimal computation offloading strategy policy, uplink subchannel allocation, uplink transmission power allocation, and computation resource scheduling. The optimization problem is decomposed into two sub-problems due to the NP-hard property. In order to analyze the offloading strategy, a sub-algorithm named distributed potential game is built. The existence of Nash equilibrium is proved. To jointly allocate uplink subchannel, uplink transmission power, and computation resource for the offloading mobile terminals, a sub-algorithm named cloud and wireless resource allocation algorithm is designed. The solutions for subchannel allocation consist of uniform zero frequency reuse method without interference and fractional frequency reuse method based on Hungarian and graph coloring with interference. A distributed JCORAO scheme is proposed to solve the optimization problem by the mutual iteration of the two sub-algorithms. Simulation results show that the distributed JCORAO scheme can effectively decrease the energy consumption and task completion time with lower complexity.

A Radio Resource Virtualization-Based RAT Selection Scheme in Heterogeneous Networks

In the future heterogeneous wireless networks, heterogeneity of radio resources from different radio access technologies (RATs) still exists. The heterogeneity, especially for networks with the coexistence of non-orthogonal and orthogonal resources, makes the radio resources difficult to be uniformly measured, and thus hinders the efficient utilization of radio resources. To overcome this limitation, this letter firstly proposes a radio resource virtualization approach in heterogeneous networks. Based on the accumulated historical data of resource utilization information, heterogeneous radio resources are virtualized into normalized resources using deep learning method. Secondly, the consumption difference of virtualized resources under different situations of network load and user demand is modeled. Moreover, aiming at efficiently utilizing radio resources and reducing access blocking rate, a RAT selection scheme based on the radio resource virtualization is proposed. Through simulation, the validity of the proposed scheme is evaluated.

A study on cell association in heterogeneous networks with joint load balancing and interference management

Exponential growth in the demand for network capacity has led to extensive research on advanced cellular network technology. A heterogeneous network in which traditional well-planned macro cell deployment is overlaid by small-scale unplanned base stations is one effective solution for next-generation networks. However, the cell association techniques currently used in macro-only cellular networks are not suitable for next-generation heterogeneous networks. Finding effective methods to handle the cell association problem in this new type of network is a hot topic of research in this field. This paper provides an overview of the cell association problem in heterogeneous networks and discusses the main issues that need to be addressed by an efficient cell association technique in order to maximize the network throughput. It has been shown that an efficient cell association scheme in heterogeneous networks must balance the load among different cells while minimizing the inter-cell interference at the same time. Jointly considering these two objectives is a challenge currently being investigated by researchers. An overview on load balancing and interference management in heterogeneous networks is provided in this paper. A review of the existing literature shows that there is a need for an efficient distributed solution in which load balancing approaches are observed and at the same time users prone to harmful interference are protected. A framework for modeling the heterogeneity of this type of network is presented, a simulation is performed in order to verify the effects of different parameters, and, finally, the problem is formulated. Future research directions are also provided in the paper.

Multiobjective Auction-Based Switching-Off Scheme in Heterogeneous Networks: To Bid or Not to Bid?

The emerging data traffic demand has caused a massive deployment of network infrastructure, including Base Stations (BSs) and Small Cells (SCs), leading to increased energy consumption and expenditures. However, the network underutilization during low traffic periods enables the Mobile Network Operators (MNOs) to save energy by having their traffic served by third party SCs, thus being able to switch off their BSs. In this paper, we propose a novel market approach to foster the opportunistic utilization of the unexploited SCs capacity, where the MNOs, instead of requesting the maximum capacity to meet their highest traffic expectations, offer a set of bids requesting different resources from the third party SCs at lower costs. Motivated by the conflicting financial interests of the MNOs and the third party, the restricted capacity of the SCs that is not adequate to carry the whole traffic in multi-operator scenarios, and the necessity for energy efficient solutions, we introduce a combinatorial auction framework, which includes i) a bidding strategy, ii) a resource allocation scheme, and iii) a pricing rule. We propose a multiobjective framework as an energy and cost efficient solution for the resource allocation problem, and we provide extensive analytical and experimental results to estimate the potential energy and cost savings that can be achieved. In addition, we investigate the conditions under which the MNOs and the third party companies should take part in the proposed auction.

A novel resource allocation algorithm based on downlink and uplink decouple access scheme in heterogeneous networks

Traditional cellular network requires that a user equipment (UE) should associate to the same base station (BS) in both the downlink (DL) and the uplink (UL). Based on dual connectivity (DC) introduced in LTE-Advanced R12, DL/UL decouple access scheme has been proposed, which is especially suitable for heterogeneous networks (HetNets). This paper is the pioneer to take the DL/UL decouple access scheme into consideration and develop a novel resource allocation algorithm in a two-tier HetNet to improve the total system throughput in the UL and ease the load imbalance between macro base stations (MBSs) and pico base stations (PBSs). A model is formulated as a nonlinear integer programming, and the proposed algorithm is a sub-optimal algorithm based on the graph theory. First, an undirected and weighted interference graph is obtained. Next, the users are grouped to let users with large mutual interferences to be assigned to different clusters. Then, the users in different clusters are allocated to different resource blocks (RBs) by using the Hungarian algorithm. Simulation results show that the proposed algorithm can provide great promotions for both the total system throughput and the average cell edge user throughput and successfully ease the load imbalance between MBSs and PBSs.

Energy efficiency enhancement in heterogeneous networks: a joint resource allocation approach

To support the drastic growth of wireless multimedia services and the requirements of ubiquitous access, numerous wireless infrastructures which consume enormous energy, such as macrocell, small cell, distributed antenna systems and wireless sensor networks, have been deployed. Under the background of environmental protection, improving the energy efficiency (EE) in wireless networks is becoming more and more important. In this paper, an EE enhancement scheme in heterogeneous networks (HetNets) by using a joint resource allocation approach is proposed. The HetNets consists of a mix of macrocell and small cells. Firstly, we model this strategic coexistence as a multi-agent system in which decentralized resource management inspired from Reinforcement Learning are devised. Secondly, a Q-learning based joint resource allocation algorithm is designed. Meanwhile, with the consideration of the time-varying channel characteristics, we take the long-term learning reward into account. At last, simulation results show that the proposed decentralized algorithm can approximate to centralized algorithm with low-complexity and obtain high spectral efficiency (SE) in the meantime.

A novel dynamic interference coordination scheme in heterogeneous networks

A novel dynamic interference coordination scheme in heterogeneous networks

Energy-Per-Bit Minimized Radio Resource Allocation in Heterogeneous Networks

In this paper, we present an energy-per-bit minimized radio resource allocation scheme in heterogeneous networks equipped with multi-homing capability, simultaneously connecting to different wireless interfaces. Specifically, we formulate an optimization problem related to minimization of energy-per-bit which takes a form of nonlinear fractional programming. Then we derive a parametric optimization problem out of that fractional programming and solve the original problem by using a double-loop iteration method. In each iteration, we derive the optimal resource allocation policy by applying Lagrangian duality and an efficient dual update method. In addition, we present suboptimal resource allocation algorithms using the properties of the optimal resource allocation policy. Numerical results reveal that the optimal allocation algorithm improves energy efficiency significantly over the existing resource allocation algorithms designed for homogeneous networks and its performance is superior to suboptimal algorithms in reducing energy consumption as well as in enhancing network energy efficiency.

Interference Mitigation through Successive Cancellation in Heterogeneous Networks

We present a practical interference management scheme for heterogeneous networks (HetNets). The underlying ideas are based on (i) Han-Kobayashi-type message splitting (MS) where the receivers decode and cancel “part” of the interference which is accordingly optimized by the transmitters to ensure decoding and (ii) opportunistic interference cancellation (OIC) where the interfering transmitters act independently of the receivers that employ interference cancellation. We develop a novel transmission and reception scheme, called joint MS and OIC (MS-OIC), that engages both MS and OIC to account for a practical HetNet system with multiple macrocells and femtocells. The MS component includes a precoder design that judiciously maximizes the weighted sum throughput via the enabling of interference cancellation. A system design along with a novel scheduler that facilitates MS-OIC in a general HetNet system is also developed. System level simulations for a general HetNet system are presented, and the proposed MS-OIC scheme is compared with benchmark schemes such as Coordinated Beamforming (CBF) and joint CBF and Almost Blank Subframes (CBF-ABS). It is observed that the proposed MS-OIC scheme improves the macrocell throughput substantially, balances the achievable rates between the macrocell and femtocell users, and provides significant outage performance improvement in the system.

A QoS-aware VoD resource sharing scheme for heterogeneous networks

In network-aware concept, applications are aware of network conditions and are adaptable to the varying environment to achieve acceptable and predictable performance. Two basic aspects of network-aware applications, network-awareness and network adaptation, have been widely addressed in the literature. In this work, a solution for video on demand service that integrates wireless and wired networks by using the network-aware concepts is proposed to reduce the blocking probability and dropping probability of mobile requests. Fuzzy logic inference system is employed to select appropriate cache relay nodes to cache published video streams and distribute them to different peers through service oriented architecture (SOA). SIP-based control protocol and IMS standard are adopted in this work to ensure the possibility of heterogeneous communication and provide a framework for delivering real-time multimedia services over an IP-based network to ensure interoperability, roaming, and end-to-end session management. The experimental results demonstrate that effectiveness and practicability of the proposed work.

Network controlled handover scheme for heterogeneous network

A new network controlled handover scheme for heterogeneous wireless networks is introduced. The scheme gives better handover delay performance with nearly the same amount of signalling in the network as currently known solutions. The trade-off between handover delay and the amount of signalling is optimised to achieve high performance of the vertical handover.