Two-tier Heterogeneous Network Research Articles

Reinforcement Learning for Self Organization and Power Control of Two-Tier Heterogeneous Networks

Self-organizing networks (SONs) can help to manage the severe interference in dense heterogeneous networks (HetNets). Given their need to automatically configure power and other settings, machine learning is a promising tool for data-driven decision making in SONs. In this paper, a HetNet is modeled as a dense two-tier network with conventional macrocells overlaid with denser small cells (e.g. femto or pico cells). First, a distributed framework based on the multi-agent Markov decision process is proposed that models the power optimization problem in the network. Second, we present a systematic approach for designing a reward function based on the optimization problem. Third, we introduce Q-learning-based distributed power allocation algorithm (Q-DPA) as a self-organizing mechanism that enables the ongoing transmit power adaptation as new small cells are added to the network. Furthermore, the sample complexity of the Q-DPA algorithm to achieve $\epsilon $ -optimality with high probability is provided. We demonstrate, at the density of several thousands femtocells per km2, the required quality of service of a macrocell user can be maintained via the proper selection of independent or cooperative learning and appropriate Markov state models.

Analysis of twin-layer cellular networks and frequency-swapping aided femtocell relying on fractional frequency reuse

In the 5th generation wireless systems, one of the effective technologies to enhance the attainable performance is to use heterogeneous networks, consist of macro base stations and low power base stations such as femto base stations. In order to achieve high spectral efficiency, as one of the most promising trends for heterogeneous networks, the low power base stations have to reuse the available spectrum of macro base stations. However, by reusing the available spectrum, the resulting co-channel interference increases the outage probability of the network. In this paper, first, a new spectrum access strategy has been proposed for a two-tier heterogeneous network consisting of distributed antenna system-aided macrocells and femtocells. Then, the outage probability of the outdoor macro users, as the main users of the network, has been investigated. The simulation results indicate that by applying the proposed spectrum access strategy, the outage probability of the outdoor macro users in the considered network will be equal to the outage probability of the outdoor macro users in the absence of femto base stations. In fact, the effect of interference from femto base stations with the outdoor macro users will be eliminated and the outage probability of the outdoor macro users will be significantly reduced comparing to the state of the art strategy.

Energy efficient SBSs sleep mode analysis for successive user association and resource scheduling algorithms in two‐tier heterogeneous network

This study analyses and compares the downlink energy efficiency (EE) of user association and resource scheduling algorithms considering sleep mode of small cell base stations (SBSs) in two-tier heterogeneous cellular networks. Owing to the NP-hardness of joint user association and resource scheduling algorithms, the authors successively perform user association and resource scheduling algorithms. Firstly, in the user association algorithms, sleep mode for the SBSs without associated users is considered to improve EE, where they associate users with the macrocell base station (MBS) or SBSs according to three signal strength strategies, namely, unbiased user association, biased user association and signal to interference plus noise ratio-based user association. Then, in the resource scheduling algorithms, they schedule the MBS and SBSs resource blocks to users based on three scheduling criteria, i.e. maximum received signal strength, round robin and proportional fairness, respectively. Fairness among users is also analysed. In the simulation, numerical results for different successive user association and resource scheduling algorithms are compared. The optimum algorithms are found in the different network environments. These results are significant for the heterogeneous network operation to get high EE.

Spectral Efficiency Analysis of the Decoupled Access for Downlink and Uplink in Two-Tier Network

This paper analyzes the efficacy of decoupled wireless access in a two-tier heterogeneous network. The decoupled wireless access and its performance benefits have been studied in different scenarios recently. In this paper, an in-depth analysis on its efficacy from spectral efficiency perspective is provided. To achieve this task, (i) new closed-form expressions for probability of association of user equipment with different tiers employing different frequency bands (i.e., microwave and millimeter wave) with different pathloss exponents are derived using univariate Fox's H-functions; (ii) Distributions of the distance to the serving base stations are also derived; (iii) Exact expressions of spectral efficiency for different association cases are further obtained using bivariate Fox's H-functions. Furthermore, rigorous simulation results are provided which validate the aforementioned analytical results. In addition to that, a detailed discussion on the decoupling gain of decoupled wireless access and its efficacy is also provided. Finally, despite the improvement provided by the decoupled wireless access, which is evident from the results presented in this paper, a few questions are raised on its pragmatic value.

AN-Aided Secure Beamforming in Power-Splitting-Enabled SWIPT MIMO Heterogeneous Wireless Sensor Networks

In this paper, we investigate the physical layer security in a two-tier heterogeneous wireless sensor network (HWSN) depending on simultaneous wireless information and power transfer (SWIPT) approach for multiuser multiple-input multiple-output wiretap channels with artificial noise (AN) transmission, where a more general system framework of HWSN only includes a macrocell and a femtocell. For the sake of implementing security enhancement and green communications, the joint optimization problem of the secure beamforming vector at the macrocell and femtocell, the AN vector, and the power splitting ratio is modeled to maximize the minimal secrecy capacity of the wiretapped macrocell sensor nodes (M-SNs) while considering the fairness among multiple M-SNs. To reduce the performance loss of the rank relaxation from the SDR technique while solving the non-convex max–min program, we apply successive convex approximation (SCA) technique, first-order Taylor series expansion and sequential parametric convex approximation (SPCA) approach to transform the max–min program to a second order cone programming (SOCP) problem to iterate to a near-optimal solution. In addition, we propose a novel SCA-SPCA-based iterative algorithm while its convergence property is proved. The simulation shows that our SCA-SPCA-based method outperforms the conventional methods.

Degrees of Freedom of 2-Tier Networks Without Channel State Information at the Transmitter

We characterize the degrees of freedom (DoF) of the two-tier heterogeneous networks without channel state information at the transmitters or cooperation among transmitters. We consider conventional transmitters while the users are equipped with a multimode receiver. In contrast to previous works focused on two-tier networks, the derived DoF consider the management of the intracell, the intercell, and intertier interference. The derived bounds define the DoF region for any two-tier network. Furthermore, these bounds are achievable by combining blind interference alignment schemes properly.

Coverage Analysis of Inter-Tier Interference Cancellation for Massive MIMO HetNet With Repulsion

The inter-tier interference cancellation (IC) by employing zero-forcing precoding method for two-tier heterogeneous network under considering repulsion between base stations (BSs) with adopting the β-Ginibre point process (β-GPP) model is investigated here. The distribution of the number of users that request IC under β-GPP model is first derived. Then, the approximation for coverage probability of the typical user with inter-tier IC is given out under massive multiple-input multiple-output (MIMO) assumption. Numerical results validate the accuracy of the approximation, and show that, compared with Poisson point process model, the β-GPP model is more accurate in prediction of the coverage probability in actual network with inter-tier IC. Furthermore, when the number of antennas in macro BS and that of users all approach infinity with fixed ratio, the coverage probability when the user is served by the macro BS can be simplified to a simple closed-form formula, which reveals the potential of massive MIMO to improve user performance under the case of large signal-to-interference ratio threshold.

Two-Stage Stable Matching Based Dynamic Spectrum Allocation in Heterogeneous Networks

This paper addresses the resource allocation problem for small cells in the two-tier heterogeneous networks (HetNets) with non-independent resource blocks (RBs) usability, which is prevalent in HetNets application. To formulate the correlations of different RBs to facilitate the resource allocation, a normalized pointwise mutual information (NPMI)-based coefficient is proposed, which is easy to compute and adapt based on the historical information about RBs usability. To obtain a fast allocation solution, a two-stage stable matching-based dynamic spectrum allocation algorithm (TSSM) is proposed, which takes both network throughput and user performance as optimization metrics. Specifically, through robust preferable stable matching in the first stage and the iterative matchings with NPMI-based coefficient as the preference profiles in the second stage, the efficient matching solution can be obtained with low complexity and thus is well adapted to the requirement of the resource allocation in HetNets. The validity of the proposed coefficient in modeling the relevance of RBs usability and the benefit of its usage in the allocation algorithm is verified with typical spectrum usability related data. The extensive simulation results on various spectrum environment show the average probability of no RB to use following the proposed TSSM are reduced by more than 13.2%, and the robust requirement for users can be guaranteed better at the same time. Furthermore, the accumulated throughput of all users in the network increases by more than 19.4% on an average under different RBs usability environment.

Fairness-Based Distributed Resource Allocation in Two-Tier Heterogeneous Networks

Booming demand for mobile intelligent terminal equipment results in the exponential growth of the data flow in the fifth-generation mobile communication network. Small-cell networks have been considered as one of the possible solutions, where interference management and effective resource allocation are outstanding issues due to numerous small base stations. In this paper, the concept of cognitive small-cell networks is introduced, which combines technologies from cognitive radio with small cells. We aim to maximize the total throughput of the cognitive small-cell networks by jointly considering interference management, fairness-based resource allocation, average outage probability, and channel reuse radius. In order to make the optimization problem tractable, we decompose the original problem into three sub-problems. First, we derive the average outage probability function of the network with respect to the spectrum sensing threshold. With a given outage probability threshold, the associated range of the channel reuse radius is obtained. In addition, to maximize the total throughput, a fairness-based distributed resource allocation (FDRA) algorithm is proposed to guarantee the fairness among cognitive small-cell base stations, which defines the satisfaction degree and the traffic requirement indicators to dynamically adjust the resource allocation process. Finally, considering the time-varying traffic load and different geographical environments, an improved FDRA (IFDRA) algorithm is proposed to further improve the throughput of the hot area. The simulation results demonstrate that the proposed FDRA algorithm and IFDRA algorithm could achieve a considerable performance improvement compared with schemes in the literature while providing better fairness among cognitive small-cell base stations.

Joint Optimization of Area Spectral Efficiency and Energy Efficiency for Two-Tier Heterogeneous Ultra-Dense Networks

Being a promising candidate technology for the fifth-generation cellular systems, the ultra-dense network (UDN) is capable of improving the system throughput by deploying more small cells (SCs) in the existing macro-cells (MCs). In most cases, base stations (BSs) from both the MCs tier and SCs tier are modeled as two independent homogeneous Poisson point processes (PPPs) or other point processes derived from a PPP. In the previous works, the area spectral efficiency (ASE) and energy efficiency (EE) are evaluated from a typical user's perspective, and this method works well in single-user scenarios. However, there are multiple users sharing spectral resources in practical cellular systems, and the above-mentioned method cannot work in these scenarios. Therefore, we investigate the ASE and EE from the perspective of a typical BS. Analytical results show that the ASE increases with the increasing SCs density, which means that deploying more SCs in the MCs coverage area is a feasible way to enhance the system throughput. However, the energy consumption of the entire network is increasing as the SCs density increases. Therefore, we employ the firefly algorithm to jointly optimize the ASE and EE for the two-tier heterogeneous UDN. Finally, the optimal system parameters can be found under two fixed weights for the ASE and EE, respectively.

Hybrid Self-Backhaul and Cache Assisted Millimeter Wave Two-Tier Heterogeneous Networks With MIMO Equipped Backhaul Access Points

This paper focuses on effective content delivering over the co-channel and full millimeter-wave (mm-Wave) heterogeneous networks (HetNets) by using hybrid self-backhaul and cache-assisted (HSBC-assisted) content delivering. Especially, the small base stations (SBSs) are equipped with a single antenna, a portion of which has the capacity-limited cache and the remaining of which has not to cache. The macro base stations (MBSs) are equipped with multiple antennas or even massive MIMO, which provide the wireless self-backhaul for the SBSs without cache. Instead of the oversimplified flat-top mm-Wave antenna pattern, a more actual and accurate one for the uniform linear array at MBSs is used. By modeling the locations of line-of-sight (LoS) and non-LoS base stations as independent Poisson point processes, this paper first presents the downlink content delivering model as well as the distributions of interferences. Then, to explore the impact of the specific MIMO self-backhaul on content delivering, a comprehensive investigation is conducted in terms of the coverage probability, achievable average area rate (AAR), average delay (AD), and energy effective (EE). The analytical and numerical results show that the utilization of multi-antenna MBSs not only improves the AAR and AD of self-backhaul transmission from MBS to SBS but also does the ones of cache and non-cache access links due to narrow beam and direction transmission decreasing interference. The results also show that in the proposed HSBC-assisted HetNets, under the scenario where the low-resolution antenna array is used and the cache capacity is large, the effect of hardware power consumption on the aggregate EE is negligible. This result shows a trade-off between AD and EE. With a projected EE, the joint utilization of cache and low-resolution antenna array allows more antennas equipped at MBSs so that the near-field propagation loss is compensated by the higher gain of directional antennas. Meanwhile, the results show that the achieved performance gain by the HSBC-assisted system over the traditional self-backhaul (TSB)-assisted greatly depends on the system parameters. With this observation, an adaptive TSB-HSBC-assisted system model is proposed. When the ratio factor of cache-assisted SBSs is less than the threshold, the sole TSB-assisted model is selected; otherwise, the HSBC-assisted model is used.

Physical Layer Security in Heterogeneous Networks With Pilot Attack: A Stochastic Geometry Approach

In this paper, we investigate physical layer security in a two-tier heterogeneous network with sub-6 GHz massive multi-input multi-output (MIMO) macro cells and millimeter wave (mmWave) small cells. By considering pilot attacks from the eavesdroppers, we analyze the coverage and secrecy performance using stochastic geometry. For the sub-6 GHz tier, we show that increasing the number of BS antennas is more effective than increasing BS density in improving the coverage performance, whereas densifying BS is more effective for security enhancement. For the mmWave tier, we first derive the success probability of beam alignment based on a beam sweeping-based channel training model. It is shown that the mmWave tier may outperform the sub-6 GHz counterpart in terms of both coverage and secrecy through densifying the base stations. Our results also reveal that the mmWave small cell can provide better coverage performance in the high transmission rate region, and can achieve higher security in the low redundant rate region, which reveals the advantage of using mmWave for secure communication. Numerical results verify the analysis.

Cache Placement in Two-Tier HetNets With Limited Storage Capacity: Cache or Buffer?

In this paper, we aim to minimize the average file transmission delay via bandwidth allocation and cache placement in two-tier heterogeneous networks with limited storage capacity, which consists of cache capacity and buffer capacity. For average delay minimization problem with fixed bandwidth allocation, although this problem is nonconvex, the optimal solution is obtained in closed form by comparing all locally optimal solutions calculated from solving the Karush–Kuhn–Tucker conditions. To jointly optimize bandwidth allocation and cache placement, the optimal bandwidth allocation is first derived and then substituted into the original problem. The structure of the optimal caching strategy is presented, which shows that it is optimal to cache the files with high popularity instead of the files with big size. Based on this optimal structure, we propose an iterative algorithm with low complexity to obtain a suboptimal solution, where the closed-from expression is obtained in each step. Numerical results show the superiority of our solution compared with the conventional cache strategy without considering cache and buffer tradeoff in terms of delay.

Dynamic Radio Resource Slicing for a Two-Tier Heterogeneous Wireless Network

In this paper, a dynamic radio resource slicing framework is presented for a two-tier heterogeneous wireless network. Through software-defined networking-enabled wireless network function virtualization, radio spectrum resources of heterogeneous wireless networks are partitioned into different bandwidth slices for different base stations (BSs). This framework facilitates spectrum sharing among heterogeneous BSs and achieves differentiated quality-of-service (QoS) provisioning for data service and machine-to-machine service in the presence of network load dynamics. To determine the set of optimal bandwidth slicing ratios and optimal BS-device association patterns, a network utility maximization problem is formulated with the consideration of different traffic statistics and QoS requirements, location distribution for end devices, varying device locations, load conditions in each cell, and intercell interference. For tractability, the optimization problem is transformed to a biconcave maximization problem. An alternative concave search (ACS) algorithm is then designed to solve for a set of partial optimal solutions. Simulation results verify the convergence property and display low complexity of the ACS algorithm. It is demonstrated that the proposed radio resource slicing framework outperforms the two other resource slicing schemes in terms of low communication overhead, high spectrum utilization, and high aggregate network utility.

Robust power allocation for two-tier heterogeneous networks under channel uncertainties

In this paper, the trade-off among system sum energy consumption and robustness is studied. In this regard, a robust power allocation problem is formulated for a two-tier heterogeneous network with uplink transmission mode and consideration of imperfect channel state information. The objective is to minimize the total transmit power of femtocell users (FUs), while the interference to macrocell user receiver is limited to a predefined interference level, the transmit power of each FU transmitter is kept within their power budgets, and the actual signal-to-interference-plus-noise ratio of each femtocell receiver is above a minimum threshold. Considering the uncertainties of the interference links from FUs to macrocell base stations and forward transmission links of each FU, the robust power allocation problem is formulated as a semi-infinite programming problem (SIPP). By the worst-case approach, the SIPP is transformed into a convex optimization problem solved by the Lagrange dual decomposition method. Moreover, the feasible regions of constraints, computational complexity, and sensitivity degree of the proposed robust algorithm are also analyzed. Simulation results investigate the impact of channel uncertainties and the superiority of the proposed algorithm by comparing with non-robust algorithm.

Queue-Aware Power Consumption Minimization in Two-Tier Heterogeneous Networks

In this paper, we study the network average power consumption minimization problem in a two-tier heterogeneous network by optimally tuning the activation ratio of micro base stations (BSs) under the quality of service (QoS) constraints of the network mean queueing delay and the network signal-to-interference ratio (SIR) coverage. With the consideration of dynamic packets arrivals, each BS can either be busy or be idle depending on its queueing status. The network performance is thus critically determined by the traffic intensity of each BS. With the assumption of universal frequency reuse, the average traffic intensity of each tier is characterized by a set of fixed-point equations, which can be solved by a proposed iterative method. By using the approximation that BSs of the same tier have the same SIR coverage, the cumulative distribution function of the traffic intensity of each tier is further obtained. On that basis, the network average power consumption per area, the network mean queueing delay, and the network SIR coverage are characterized. Numerical results demonstrate that if the idle power coefficient is below a certain threshold, then the optimal activation ratio equals the one to minimize the network average power consumption per area; otherwise, the optimal activation ratio can be obtained according to the QoS constraints. It is further shown that universal frequency reuse outperforms spectrum partitioning in terms of both the network average power consumption and the network SIR coverage in the considered scenario.

Security analysis for interference management in heterogeneous networks

Heterogeneous network (HetNet) is recognized as a promising technique to provide blanket wireless coverage and high throughput in 5G wireless networks. With the heterogeneous characteristics, HetNet achieves higher capacity, wider coverage and better performance in energy efficiency and spectrum efficiency. However, HetNet also brings complex interference management in the network. In this paper, we present a security analysis for a proposed interference management mechanism in a two-tier heterogeneous network (HetNet) system. The proposed interference management mechanism aims to maximize the secrecy rate of a cellular user under eavesdropping attack. The HetNet system model includes a macro base station, several small base stations, several users, and one eavesdropper. To further improve the performance of the network, massive multiple-input multiple-output technology is applied to base stations. A single antenna is applied to users and the eavesdropper. Device-to-device (D2D) communications are considered in the HetNet system model for introducing interference in the macro cell to the eavesdropper. The proposed interference management mechanism takes consideration of three factors as transmit beamforming, spectrum reuse and D2D communications. Not only the secrecy rate of the user under eavesdropping attack but also the communication quality of services of SBSs users are considered in the security analysis. An optimization problem is formulated for the secrecy rate maximization of the user under eavesdropping attack with the constraints of quality of services of users associated with base stations and power limitation of base stations. The security analysis and numerical results show that our proposed interference management mechanism for physical layer security can utilize the interference in the network to improve the secrecy rate of the cellular user under eavesdropping attack.

A Novel Cooperative Non-Orthogonal Multiple Access (NOMA) in Wireless Backhaul Two-Tier HetNets

In this paper, we propose to re-engineer the wireless backhaul two-tier heterogeneous networks architecture by developing a novel cooperative transmission scheme based on non-orthogonal multiple access (NOMA). To effectively manage severe interference from the newly introduced backhaul communications, we employ the cochannel time division duplexing combined with spectrum partitioning between two considered tiers. This paper’s novelty lies in the formulation to solve for the NOMA decoding order, which affects the rule of the cooperation between small cell transmissions. We propose two optimization problems of jointly designing the NOMA decoding order together with the transmit beamforming at the macro base station and power allocation at the small cells which maximize the total achievable rate and the number of satisfied users, respectively. The first and second formulated problems are both mixed integer non-convex and are generally NP-hard. To solve them, we first employ the difference of convex functions to present the formulated binary variables and then equivalently transform the optimization problems into more tractable forms. Finally, we develop an iterative low-complexity algorithm based on successive convex approximation technique and majorization minimization method, which is provable to eventually converge at a sub-optimal solution. Numerical results are extensively studied to corroborate that our proposed strategy outperforms the conventional designs in terms of total achievable rate and number of satisfied users.

A QEE-Oriented Fair Power Allocation for Two-tier Heterogeneous Networks

In future wireless network, user experience and energy efficiency will play more and more important roles in the communication systems compared to their roles at present. Quality of experience (QoE) and Energy Efficiency (EE) become the widely used metrics. In this paper, we study a combinatorial problem of QoE and EE and investigate a fair power allocation in heterogeneous networks. We first design a new metric, QoE-aware EE (QEE) to reflect the relationship of QoE and energy. Then, the concept of Utopia QEE is introduced, which is defined as the achievable maximum QEE in ideal conditions, for each user. Finally, we transform the power allocation process to an optimization of ratio of QEE and Utopia QEE and use invasive weed optimization (IWO) algorithm to solve the optimization problem. Numerical simulation results indicate that the proposed algorithm can get converged and efficiently improve the system energy efficiency and the QoE for each user.

Zone-based load balancing in two-tier heterogeneous cellular networks: a game theoretic approach

In this paper, load balancing in two-tier cellular networks is investigated. The network under-study is divided into several zones. The first tier of each zone includes a heavy-loaded Macrocell (i.e., the central cell) and its neighboring cells. The second tier includes Picocells in the area of the zone. We model the load balancing problem in each zone as a Cournot game where the optimal load distribution of each cell is the Nash Equilibrium Solution (NES) of the game. Since the actual load of each cell depends on the initial placement of users and their mobility pattern, a load balancing algorithm called Weighted Distributed Heterogeneous Zone based Load Balancing (W-DHZLB) is proposed which transfers loads between over-loaded and under-loaded cells aiming at approximating the obtained NES. In order to avoid ping-pong effect during hand-overs, inner users are given a higher priority to join a Macrocell compared to the users locating on the edge of the same Macrocell. Therefore, when loads are transferred to a Picocell, it is more likely one of the internal users of the corresponding Macrocell rather than users residing in the neighboring Macrocell. The proposed algorithm reduces the risk of epidemic unbalanced load distribution in heterogeneous networks. Simulation results show that W-DHZLB outperforms a previous load balancing algorithm in the literature.