Dense Heterogeneous Cellular Networks Research Articles

Enhanced performance of long-term evolution small-cell networks using improved mobility algorithms

With an ever-increasing number of user equipment (UE) and bandwidth demands of new applications, the deployment of dense heterogeneous cellular networks has been adopted in many network scenarios. The small cells are unable to unload the traffic due to the random UEs mobility and cells deployment. This degrades the network performance such as handover success, throughput, and load distribution. To address such a problem, we propose an enhanced mobility load-balancing algorithm for small cells. The conventional mobility load balancing (MLB) algorithms study only the fixed or adaptive thresholds of the network separately to consider the load balance process, while other MLB algorithms consider the neighboring cells of the network those experience unnecessary MLB actions. The proposed load balancing algorithms study overloaded cells and neighbors using the proposed efficiency parameter, B. To identify the overloaded cells, we propose B which compares between a pre-defined threshold and the network threshold to categorize medium and overloaded cells, based on B, the algorithm is triggered. Then, to control the shifted load to a target neighbor cell, we propose the Rescue factor, f. the f ensures the load of the target cell after handover is equal or less than Ɓ. The simulation results showed a lower standard deviation and higher throughput and physical resource block utilization than surveyed algorithms.

Secrecy‐oriented user association in ultra dense heterogeneous networks against strategically colluding adversaries

Network densification is recognized as the key technology to meet the ever growing demand of data traffic in next generation wireless networks. However the proliferation of small cell base stations (SCBSs) introduces vulnerabilities to information security, as they are prone to eavesdropping attacks. In this paper, it is studied how user association strategies can be specifically tailored to meet this security challenge in a ultra dense heterogeneous cellular network(UDHCN) with a group of colluding eavesdroppers. In particular, the situation is considered where eavesdroppers may have limited capabilities in intercepting and decoding data traffic. In this setting each eavesdropper has to make its own decision on eavesdropping targets, and they are able to take concerted actions to sabotage information security. To address this challenge, a zero sum game framework to reflect the conflicting interests of users and eavesdroppers is proposed and a user association scheme is devised that aims to maximize system sum secrecy rate against these adversaries whose actions intend to minimize sum secrecy rate. The case that all adversaries have limited eavesdropping capabilities is first considered, and it is shown that the corresponding zero sum game is indeed a bilinear game, and its Nash equilibrium solution can be readily approximated using a saddle point Frank Wolfe(SP-FW)algorithm. Then the framework is extended to the case where adversaries with a diverse configuration of eavesdropping capabilities exist. In this case, it is shown that the underlying minimax optimization problem is indeed a nonsmooth convex-nonconcave one. A two stage method is proposed by first smoothing the objective function with a Hermite cubic polynomial approximation, and then obtaining a nearly stationary solution via a recently proposed proximal point gradient descent method. Simulation results show that the proposed framework leads to significant increases in sum secrecy rate and secrecy probability against both the capability-limited adversaries and a hybrid type of adversaries.

SMDP-based sleep policy for base stations in heterogeneous cellular networks

A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage. It is a key technology for the new generation of the mobile communication system. The dense deployment of small base stations not only improves the quality of network service, but also brings about a significant increase in network energy consumption. This paper mainly studies the energy efficiency optimization of the Macro-Femto heterogeneous cellular network. Considering the dynamic random changes of the access users in the network, the sleep process of the Femto Base Stations (FBSs) is modeled as a Semi-Markov Decision Process (SMDP) model in order to save the network energy consumption. And further, this paper gives the dynamic sleep algorithm of the FBS based on the value iteration. The simulation results show that the proposed SMDP-based adaptive sleep strategy of the FBS can effectively reduce the network energy consumption.

Cluster-Based Load Balancing Algorithm for Ultra-Dense Heterogeneous Networks

In a highly dense heterogeneous cellular network, the loads across cells are uneven due to random deployment of cells and the mobility of user equipments (UEs). Such unbalanced loads result in performance degradation such as throughput and handover success. In order to solve the uneven load problem for better network performance, we propose a cluster-based mobility load-balancing algorithm for heterogeneous cellular networks. Traditional mobility load balancing (MLB) schemes that consider only the adjacent neighbors cannot provide enough improvement in network performance. On the other hand, the previous MLB schemes consider neighbors in the entire network suffer from unnecessary MLB actions. However, in the load balancing process, the proposed algorithm considers overloaded cells and their neighbors within then-tiers. First, the algorithm models the network as a directed multi-graph and constructs clusters taking the overloaded cells and their n-tier neighbors. Therefore, by adjusting cell individual offset parameters of the cells in the clusters the algorithm achieves load balancing locally. Since load balancing is performed inside the clusters, the network can be optimized more efficiently by avoiding unnecessary MLB actions. Simulations show that the proposed algorithm distributes the load across the network more evenly than other MLB algorithms, and in a low UE velocity scenario, it increases the overall network throughput by 6.42% compared to a non-optimized network without an MLB algorithm.

Uplink coverage probability and spectral efficiency for downlink uplink decoupled dense heterogeneous cellular network using multi-slope path loss model

Low powered node densification leading to dense and ultra dense heterogeneous networks is a feature of 5th generation cellular networks. With this densification, the nature of the link between the transmitter and receiver in the network requires even more accurate and reliable models. For performance analysis of such networks where the rates of signal loss over distance becomes a significant parameter, more accurate path loss models should be used when analyzing user equipment (UE) association probability, coverage probability and average spectral efficiency. In this paper, we have considered a two-tier dense heterogeneous cellular network incorporating downlink uplink decoupled technique and have derived generalized expressions for UE association probability, decoupled uplink coverage probability and decoupled uplink average spectral efficiency using multi-slope path loss model. This path loss model broadly incorporates the effects of physical environment on the distance-dependent path loss. For simulation purpose, we have compared network performance while considering single-slope and dual-slope path loss models. The derived analytical expressions have been validated through network simulations and found in good agreement. Through comparison, it has been found that the decoupled UE association probability and uplink coverage probability is higher when incorporating multi-slope path loss model as compared to single-slope path loss model while the decoupled uplink spectral efficiency is observed to be lower when incorporating dual slope path loss model.

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.

Impact of Frequency Reuse and Flexible Cell Association on the Performance of Dense Heterogeneous Cellular Networks Using Dual-Slope Path Loss Model

Impact of Frequency Reuse and Flexible Cell Association on the Performance of Dense Heterogeneous Cellular Networks Using Dual-Slope Path Loss Model

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 ...

Edge Caching in Dense Heterogeneous Cellular Networks With Massive MIMO-Aided Self-Backhaul

This paper focuses on edge caching in dense heterogeneous cellular networks, in which small base stations (SBSs) with limited cache size store the popular contents, and massive multiple-input multiple-output (MIMO)-aided macro base stations provide wireless self-backhaul when SBSs require the non-cached contents. Our aim is to address the effects of cell load and hit probability on the successful content delivery (SCD) and present the minimum required base station density for avoiding the access overload in an arbitrary small cell and backhaul overload in an arbitrary macrocell. The achievable rate of massive MIMO backhaul without any downlink channel estimation is derived to calculate the backhaul time, and the latency is also evaluated in such networks. The analytical results confirm that hit probability needs to be appropriately selected in order to achieve SCD. The interplay between cache size and SCD is explicitly quantified. It is theoretically demonstrated that when non-cached contents are requested, the average delay of the non-cached content delivery could be comparable to the cached content delivery with the help of massive MIMO-aided self-backhaul, if the average access rate of cached content delivery is lower than that of self-backhauled content delivery. Simulation results are presented to validate our analysis.

Performance Analysis of the Idle Mode Capability in a Dense Heterogeneous Cellular Network

In this paper, we study the impact of the base station (BS) idle mode capacity (IMC) on the network performance of multi-tier and dense heterogeneous cellular networks (HCNs) with both line-of-sight (LoS) and non-line-of-sight transmissions. Different from most existing works that investigated network scenarios with an infinite number of user equipments (UEs), we consider a more practical set-up with a finite number of UEs in our analysis. Moreover, in our model, the small BSs (SBSs) apply a positive power bias in the cell association procedure, so that macrocell UEs are actively encouraged to use the more lightly loaded SBSs. In addition, to address the severe interference that these cell range expanded UEs may suffer, the macro BSs (MBSs) apply enhanced inter-cell interference coordination, in the form of almost blank subframe (ABS) mechanism. For this model, we derive the coverage probability and the rate of a typical UE in the whole network or a certain tier. The impact of the IMC on the performance of the network is shown to be significant. In particular, it is important to note that there will be a surplus of BSs when the BS density exceeds the UE density, and thus a large number of BSs switch off. As a result, the overall coverage probability, as well as the area spectral efficiency, will continuously increase with the BS density, addressing the network outage that occurs when all BSs are active and the interference becomes LoS dominated. Finally, the optimal ABS factors are investigated in different BS density regions. One of major findings is that MBSs should give up all resources in favor of the SBSs when the small cell networks go ultra-dense. This reinforces the need for orthogonal deployments, shedding new light on the design and deployment of the future 5G dense HCNs.

A Tractable Framework for the Analysis of Dense Heterogeneous Cellular Networks

This paper investigates the downlink performance of dense $K$ -tier heterogeneous cellular networks (HCNs) under general settings. First, Gaussian approximation bounds for the standardized aggregate wireless interference (AWI) in dense $K$ -tier HCNs are obtained for when base stations (BSs) in each tier are distributed over the plane according to a spatial and general Poisson point process. The Kolmogorov–Smirnov (KS) distance is used to measure deviations of the distribution of the standardized AWI from the standard normal distribution. An explicit and analytical expression bounding the KS distance between these two distributions is obtained as a function of a broad range of network parameters, such as per-tier transmission power levels, per-tier BS intensity, BS locations, general fading statistics, and general bounded path-loss models. Bounds achieve a good statistical match between the standardized AWI distribution and its normal approximation even for moderately dense HCNs. Second, various spatial performance metrics of interest, such as outage capacity, ergodic capacity, and area spectral efficiency in the downlink of $K$ -tier HCNs for general signal propagation models are investigated by making use of the derived distribution approximation results. Considering two specific BS association policies, it is shown that the derived performance bounds track the actual performance metrics reasonably well for a wide range of BS intensities, with the gap among them becoming negligibly small for denser HCN deployments. Finally, both analytical and numerical results on the area spectral efficiency reveal a non-linear growth trend with diminishing returns of HCN performance. Hence, the ${\sf SIR}$ invariance property does not hold under bounded path-loss models, which is a critical finding from the HCN design perspective. In particular, it points out a critical BS density beyond which the HCN performance starts to decline due to excessive wireless interference.

Cell Association in Dense Heterogeneous Cellular Networks

Coverage evaluation of heterogeneous multi-tier cellular networks (HetNets) is often based on simplifying assumptions on cell association (CA): the resource required by, and practical limitations of pilot measurements are overlooked. Also, the base station (BS) providing the strongest signal-to-interference ratio among all BSs is always the serving BS (an ideal CA (iCA)). Consequently, the resultant analysis falls short of characterizing HetNets’ coverage in practical settings. We therefore propose an analytical framework for modeling a practical CA (pCA) by considering pilot measurement, pilot sensitivity at the users, and the number of pilot measurements, $K_P$ . Using tools from stochastic geometry, we obtain the coverage with pCA in both Rayleigh and Nakagami environments. We propose an algorithm to obtain the optimal $K_P$ and its partitioning among the BSs in different tiers that maximizes the coverage. Our analysis provides key insights in designing dense HetNets. For dense networks, scale invariance achievable under iCA is shown unsustained with pCA. Also, dense HetNets are pilot-neutral, and hence their performance is not affected by pilot sensitivity. Our extensive simulations confirm the accuracy of our analysis and the proposed algorithm, and demonstrate the effect of pCA in comparison with iCA.

A Novel Architecture for 5G Ultra Dense Heterogeneous Cellular Network

The mounting use of wireless devices and wide range applications in an ultra-dense heterogeneous wireless network has directed to the challenging circumstances that could not be handled till 4G. In order to deal with the critical challenges, the fifth generation (5G) wireless network architecture requires an efficient well-organized wireless network. In this paper, a novel architecture for the 5G ultra-dense heterogeneous cellular network is proposed. In the proposed architecture two main aspects, massive MIMO-OFDMA and IP-based vertical handover are considered. In order to have full network coverage, the whole macro area network is divided into the microcells and each microcell is further divided into the smaller cells. The heterogeneity of different types of base stations (macro area network base station, micro-cell base station, and small cell base station) provides efficient network coverage. By reducing the area of the cell, the frequency efficiency and network coverage are improved. All the base stations are equipped with the massive MIMO-OFDMA antennas and different radio access technologies so a single wireless device can switch from one radio access technology to the other. In order to prevent the link disconnection and save IP address, whenever wireless devices need to perform vertical handover first a new connection is established with new radio access technology. It is important to note the same IP address is used whereas the current connection is disconnected. By utilizing IP-based vertical handover, the new 5G wireless network can become the principal goal of service continuity and minimize the handover processing delay. The simulation results show the improvement in the network performance.

User Association and Base Station Sleep Management in Dense Heterogeneous Cellular Networks

User Association and Base Station Sleep Management in Dense Heterogeneous Cellular Networks

User Association in Energy-Aware Dense Heterogeneous Cellular Networks

Mobile traffic demand has been increasing exponentially over the last few years and forecasts show that this trend will continue in the foreseeable future. As a result, operators are forced to densify and upgrade their networks to meet this demand. This has created concerns, such as increasing greenhouse gas emissions, high capital expenditures, and associated energy costs. This paper uses tools from stochastic geometry to analyze and formulate energy-efficient deployment strategies for multi-tier heterogeneous networks (HetNets) using various user association schemes. We use simple approximations to combine the required base station (BS) density and associated transmit power per tier subject to both coverage probability and average user rate constraints. In this paper, this combination is called the deployment factor and it can be expressed in closed form for unbiased HetNets. We then formulate area power consumption (APC) minimization framework, which optimizes the deployment factor to derive specific optimal BS density and transmit power values. Furthermore, we perform a comprehensive study of the effect of biasing on the APC performance of biased HetNets. Our results show that for HetNets using the maximum average-biased-received-power association scheme, significant energy savings are possible with appropriate biasing.

Energy-aware deployment of dense heterogeneous cellular networks with QoS constraints

The base station (BS) configuration is a key factor to improve energy efficiency (EE). In this paper, we focus on designing the network deployment parameters (i.e., BS densities) for biased $K$-tier heterogeneous cellular network (HCN) with quality of service (QoS) provisioning. Using appropriate approximations, we derive the closed-form expressions of optimal BS density across all tiers to minimize the area power consumption (APC) by applying the stochastic geometry theory, while satisfying the users QoS requirements. These results are used to obtain some new insights into the EE performance of biased HCN deployment. With the aid of this approach, the best type of BSs to be deployed or switched off for energy saving purposes can be identified from the perspectives of BS transmission power. More precisely, if the BS transmission power ratio between an arbitrary pair of tiers of $K$-tier HCN, e.g., the small cell BS and macro BS tiers, is higher than a threshold which is a function of path loss exponent, bias factor and power consumption, the small cell BSs are preferred. The opposite situation takes place otherwise. Furthermore, it is also shown that, compared to the unbiased HCN scenario, significant energy savings are possible by appropriately biasing the HCN and optimizing the BS density, subject to the QoS constraints among all tiers.

Joint Rate and SINR Coverage Analysis for Decoupled Uplink-Downlink Biased Cell Associations in HetNets

Load balancing by proactively offloading users onto small and otherwise lightly-loaded cells is critical for tapping the potential of dense heterogeneous cellular networks (HCNs). Offloading has mostly been studied for the downlink, where it is generally assumed that a user offloaded to a small cell will communicate with it on the uplink as well. The impact of coupled downlink-uplink offloading is not well understood. Uplink power control and spatial interference correlation further complicate the mathematical analysis as compared to the downlink. We propose an accurate and tractable model to characterize the uplink $\textnormal{\texttt{SINR}}$ and rate distribution in a multi-tier HCN as a function of the association rules and power control parameters. Joint uplink-downlink rate coverage is also characterized. Using the developed analysis, it is shown that the optimal degree of channel inversion (for uplink power control) increases with load imbalance in the network. In sharp contrast to the downlink, minimum path loss association is shown to be optimal for uplink rate. Moreover, with minimum path loss association and full channel inversion, uplink $\textnormal{\texttt{SIR}}$ is shown to be invariant of infrastructure density. It is further shown that a decoupled association —employing differing association strategies for uplink and downlink—leads to significant improvement in joint uplink-downlink rate coverage over the standard coupled association in HCNs.