Cell Range Expansion Research Articles

Data-Driven Configuration of Interference Coordination Parameters in HetNets

The heterogeneous networks (HetNets) performance is highly dependent on the interference coordination among cells since both macrocells and small cells share the same spectrum. This paper focuses on the configuration of eICIC parameters: almost blank subframe ratio and cell range expansion bias defined for LTE-A. We propose an online learning mechanism based on a big data-driven framework and multiarmed bandit algorithms that retrieves data from the network to learn efficient configurations of eICIC parameters without requiring any previous knowledge about the network (e.g., traffic load, topology, scheduling algorithm). Our numerical results show that our approach attains a significant improvement with respect to the state of the art of online learning algorithms in networks under stationary and variable conditions (e.g., number of small cells, traffic load).

FdICIC: Inter-cell Interference Coordination for Full-Duplex Cellular Systems

This paper investigates the inter-cell interference coordination (ICIC) for heterogeneous networks (HetNets) with full-duplex (FD) small cell base stations to maximize the overall system throughput. To be compatible with the enhanced ICIC (eICIC) and the further enhanced ICIC (FeICIC) of existing LTE standards, the proposed FdICIC technique adopts cell range expansion and almost blank subframe to deal with the complicated interference scenario in such FD HetNets. In detail, the FdICIC includes four steps, namely, choosing the serving base station, pairing users for FD communication, resource block (RB) allocation, and power control of FD users. Through numerical simulation, we demonstrate that: (1) the overall system throughput can be improved by 10–25% with four FD small cell base stations when the residual self-interference is between − 130 to − 110 dB, (2) by carefully selecting the CRE bias, the overall system throughput can be further improved by about 30%, (3) the proposed user pairing, RB allocation, and power control steps have significant contributions to the performance improvement.

A dynamic CRE and ABS scheme for enhancing network capacity in LTE-advanced heterogeneous networks

With the ever-growing popularity of wireless multimedia services, wireless network base stations are increasingly likely to overload in high population density areas. An economical means exists for operators to establish more picocells in order to reduce the user traffic load on base stations and increase system capacity; however, inter-cell interference is a challenge in such heterogeneous networks. This study proposes a novel scheme that integrates dynamic cell range expansion (CRE) and dynamic almost blank subframe (ABS) schemes based on 3GPP R10 eICIC. The proposed scheme can automatically adjust the CRE bias value according to the cell traffic load, thereby ensuring that users have access to sufficient resources to transmit data when they are offloaded to a smaller cell. Furthermore, the proposed ABS scheme can determine the ABS ratio that yields the highest system capacity. The proposed CRE scheme ensures that offloaded users always have access to sufficient resources. The proposed CRE and ABS scheme can improve network system capacity by more than 13.9% of 3GPP R10 and 11.7% of the competing algorithm.

Energy Efficient Pico Cell Range Expansion and Density Joint Optimization for Heterogeneous Networks with eICIC.

Heterogeneous networks, constituted by conventional macro cells and overlaying pico cells, have been deemed a promising paradigm to support the deluge of data traffic with higher spectral efficiency and Energy Efficiency (EE). In order to deploy pico cells in reality, the density of Pico Base Stations (PBSs) and the pico Cell Range Expansion (CRE) are two important factors for the network spectral efficiency as well as EE improvement. However, associated with the range and density evolution, the inter-tier interference within the heterogeneous architecture will be challenging, and the time domain Enhanced Inter-cell Interference Coordination (eICIC) technique becomes necessary. Aiming to improve the network EE, the above factors are jointly considered in this paper. More specifically, we first derive the closed-form expression of the network EE as a function of the density of PBSs and pico CRE bias based on stochastic geometry theory, followed by a linear search algorithm to optimize the pico CRE bias and PBS density, respectively. Moreover, in order to realize the pico CRE bias and PBS density joint optimization, a heuristic algorithm is proposed to achieve the network EE maximization. Numerical simulations show that our proposed pico CRE bias and PBS density joint optimization algorithm can improve the network EE significantly with low computational complexity.

Performance Study of Uplink and Downlink Splitting in Ultradense Highly Loaded Networks

This paper provides new insights into the performance of Uplink and Downlink Splitting (UDS) in highly loaded wireless communication systems, in terms of both serving nodes and the number of users with high traffic activity. The study puts special focus on the gains that UDS could bring in terms of SINR and throughput when compared with systems with cell range expansion (CRE) in the classic downlink based cell association. CRE not only helps to offload users from macro‐ to pico‐eNBs, but also improves UL service. Instead of an aggregated throughput analysis, a detailed classification of users is performed to figure out the causes of users’ gain or loss after applying each strategy at the system level. Results show marginal gains of a pure path loss based UDS when compared with the intrinsic UL gains of CRE. Given the extra flexibility in radio resource management that splitting both links could bring, using an individual UL adjustable cell offset appears to be an interesting strategy to allow for a finer control of UL interference. The dependency of UDS performance with small cell density has also been a matter of study. Results show that the gains of UDS do decrease after a certain density of pico‐cells is surpassed.

Load-Balancing Scheme With Small-Cell Cooperation for Clustered Heterogeneous Cellular Networks

In this paper, a joint user association (UA) scheme with JP-CoMP using a hybrid self-organizing network (SON) is proposed for a practical clustered heterogeneous cellular network (cHCN) to maximize the network-wide proportional fairness among users. The cell range expansion and the enhanced intercell interference coordination have been considered as key items in the long-term evolution-advanced to offload macrocell users to small-cell base stations (sBSs). However, in a cHCN where sBSs are not distributed at random but are clustered instead, the coverage of inner sBSs in a small-cell cluster would be hardly expanded and an increased bias may result in much poor link quality as well as much higher load in outer sBSs. Thus, the load-balancing capability becomes much lower than expected in a cHCN. In order to cope with such a problem, a network architecture and protocol for the cHCN is suggested, and a feasible suboptimal iterative algorithm for determining the joint UA solution of the proposed hybrid SON is provided. It is shown that the proposed hybrid SON scheme with the proposed joint UA solution is very effective in handling the load balancing in a practical cHCN not only improving the performance of the inner sBS users by reducing the intercell interference, especially for intratier offloaded users, but also enabling more aggressive intertier offloading by effectively improving the link quality of cluster edge users without causing an unnecessary resource waste.

An Evolutionary Game Theory Approach for Joint Offloading and Interference Management in a Two-Tier HetNet

In this paper, we present a price-based approach for offloading macro users to small-cells in a two-tier heterogeneous network (HetNet). We have constructively exploited the small-cell density in a HetNet to harness offloading opportunities for macro users (MUs), the goal of which is to solve two problems simultaneously. It aims to shun the MUs, who have a lower received data rate due to the interference perceived from the small-cell tier. The scheme also fends off congestion in a macrocell, by offloading macro users to the small-cell tier. We have proposed a novel threshold pricing scheme, which a macrocell adopts, with a view to influencing low data rate MUs to join a small-cell network. Small-cell networks also charge a price, which includes an access price and an interference compensation price, proportional to the number of MUs who choose the small-cells instead of the macrocellular network. We assume that the small-cells adopt existing cell range expansion techniques to accommodate MUs. We formulate an evolutionary game to model and analyze the behavioral dynamics of the large number of MUs under the proposed pricing strategies of both networks. Replicator dynamics is used to find the evolutionary equilibrium of the evolutionary game. Sequentially, we provide the proof of the existence, uniqueness and stability of the evolutionary equilibrium through extensive analysis. Numerical results are provided to demonstrate that the proposed pricing strategies are able to shape the network dynamics by fine-tuning the rate-threshold and price. The ability to control the macrocell population share by itself with an application of the proposed pricing scheme remains the prime contribution of this paper.

Cell Selection and Resource Allocation in LTE-Advanced Heterogeneous Networks

A LTE-advanced heterogeneous network consists of many macrocells, and within each macrocell, there can have many picocells and user equipments (UEs). A UE within a macrocell can request resource blocks (RBs) from either the macrocell or a picocell within the macrocell. In this paper, two optimal problems are defined for the association of UEs, RBs, and heterogeneous cells. We show that both problems are equivalent to a 0/1 knapsack problem and, therefore, can be solved in pseudo-polynomial time by dynamic programming. Based on above two optimal problems, we, then, propose a cell selection and resource allocation (CSRA) scheme to solve the problem of allocating a UE to its macrocell or to a picocell within the macrocell. The design goal of picocells is to unload the traffic for the macrocell. When there are available RBs and UEs within the picocell, the CSRA scheme offloads UEs to the picocell to release the most number of RBs for the macrocell. Only when there are not enough RBs within a picocell and there are available RBs within the macrocell, for load balancing, the CSRA scheme moves some UEs to the macrocell. The CSRA scheme stops whenever the picocell is not overloaded or the macrocell does not have available RBs. Simulation results show that our proposed scheme performs better than the cell range expansion scheme in terms of goodput, loss rate, and delay.

Multichannel analysis of soft frequency reuse and user association in two-tier heterogeneous cellular networks

The cell range expansion (CRE) is encouraged to be applied in the heterogeneous cellular networks (HCNs), to enhance the capacity by offloading macro users to small cells. However, the enhanced inter-cell interference coordination (eICIC) techniques are supposed to be used for mitigating the strong cross-tier interference suffered by the offloaded users and small cell edge users. To address this, a novel soft frequency reuse (SFR) scheme is adopted in this paper. We analyze multichannel downlink scenarios for the SFR scheme using the tools of stochastic geometry. In consideration of the random resource allocation and practical cell load model, the analytical results of coverage probability and average user rate are derived and validated through Monte Carlo methods. Furthermore, our results can reduce to simple closed-form under reasonable special case for modern urban cellular networks. The main evaluation of the performance in terms of average user rate is presented, and the optimal combination of association bias and parameters of the SFR scheme is also investigated. Numerical results show that the SFR scheme outperforms the frequency resource partitioning (FRP) scheme in any load condition. Moreover, the CRE with SFR scheme can improve the average user rate significantly.

Coverage and Association Bias Analysis for Backhaul Constrained HetNets with eICIC and CRE

Heterogeneous networks (HetNets) are envisioned as a key solution to address the ever increasing capacity demand in wireless networks. With the deployment of enhanced radio access technologies, the non-ideal backhaul will become a potential network bottleneck. However, the impact of backhaul capacities (BCs) on the network coverage and offloading are not well understood. To address these issues, using tools from stochastic geometry, we propose a tractable framework for analyzing the impact of BCs on the network coverage and the optimal offloading bias in HetNets with cell range expansion (CRE) and time domain enhanced inter-cell interference coordination (eICIC) techniques. Conditioned on guaranteeing the minimum quality of service (QoS) of serving users, the coverage probability is derived as a function of offloading bias and BC parameters. We show how non-ideal backhaul alters the network coverage and the optimal bias. Compared with the perfect backhaul case, the optimal coverage and the optimal bias exhibit different behaviors in the case of limited BC.

Exploiting LTE-Advanced HetNets and FeICIC for UAV-Assisted Public Safety Communications

Ensuring ubiquitous mission-critical public safety communications (PSC) to all the first responders in the public safety network (PSN) is crucial at an emergency site. Recently, the use of unmanned aerial vehicles (UAVs) has received extensive interest for PSC to fill the coverage holes and establish reliable connectivity. The UAVs can be deployed as unmanned aerial base stations (UABSs) as part of a heterogeneous network (HetNet) PSC infrastructure. In this article, we address the inter-cell interference limiting factor in LTE-Advanced HetNets by applying 3GPP Release-11 further-enhanced inter-cell interference coordination (FeICIC) and cell range expansion (CRE) to enhance the system-wide spectral efficiency (SE). Through simulation with different path-loss models, we compare the system-wide 5th percentile SE when UABSs are deployed in a hexagonal grid and when their locations are optimized using a genetic algorithm, while also jointly optimizing the CRE and the FeICIC parameters. Our results show that at optimized UABS locations, the 3GPP Release-11 FeICIC with reduced power subframes can provide considerably better 5th percentile SE than the 3GPP Release-10 with almost blank subframes

Heterogeneous Cellular Networks With Spatio-Temporal Traffic: Delay Analysis and Scheduling

Emergence of new types of services has led to various traffic and diverse delay requirements in fifth generation (5G) wireless networks. Meeting diverse delay requirements is one of the most critical goals for the design of 5G wireless networks. Though the delay of point-to-point communications has been well investigated, the delay of multi-point to multi-point communications has not been thoroughly studied since it is a complicated function of all links in the network. In this work, we propose a novel tractable approach to analyze the delay in the heterogenous cellular networks with spatio-temporal random arrival of traffic. Specifically, we propose the notion of \emph{delay outage} and evaluated the effect of different scheduling policies on the delay performance. Our numerical analysis reveals that offloading policy based on cell range expansion greatly reduces the macrocell traffic while bringing a small amount of growth for the picocell traffic. Our results also show that the delay performance of round-robin scheduling outperforms first in first out scheduling for heavy traffic, and it is reversed for light traffic. In summary, this analytical framework provides an understanding and a rule-of-thumb for the practical deployment of 5G systems where delay requirement is increasingly becoming a key concern.

Virtual Soft-Handoff for Cellular Heterogeneous Networks

Cellular heterogeneous networks (HetNets), which are realized through shared carrier deployments of macrocells and small cells, are widely seen as a potential solution to serve growing data capacity demands. While these networks pose significant challenges in interference management, much of the focus in earlier efforts has been limited only to small-cell range expansion in the downlink. In this paper, we provide a comprehensive analysis of interference management techniques applicable to the uplink of cellular HetNets, with the goal of characterizing and improving edge user (e.g., 5th percentile) performance. In particular, we propose and study virtual soft-handoff (VSHO), which offers a low-complexity and low-overhead solution that exploits the link asymmetry observed in the uplink geometry of HetNets. VSHO exploits the fact that, in the uplink, an edge macro user who suffers from very low throughput may be closer to a nearby small cell than its own macrocell. The intuition is that such macro users should have better decoding opportunity when their signals are processed at the nearby small cell with better channel conditions. We also study how interference cancelation (IC) and interference avoidance through resource blanking can be incorporated into our VSHO proposal for further throughput gains. In addition to the VSHO techniques outlined in this paper, we also analyze other candidate techniques available in the Third Generation Partnership Project Long-Term Evolution (3GPP-LTE), such as cell-range expansion (CRE) and joint processing, to present a unified view of interference management options available in HetNets.

Gibbs-Sampling-Based CRE Bias Optimization Algorithm for Ultradense Networks

Cell range expansion (CRE) is an effective technique in the ultradense network (UDN) to enlarge small cells' ranges and promote network utility such as system throughput, number of users lower than a rate threshold, and proportional fairness. Due to the coupled relationship of user association and scheduling in rate-related utility optimization, optimal cell-specific CRE bias is difficult to achieve. This paper first proposes a centralized CRE bias adjusting algorithm based on Gibbs sampling to achieve the optimal solution of cell-specific CRE bias based on global information. After that, a decentralized Gibbs-sampling-based CRE bias adjusting algorithm without the need for the entire knowledge of global channel gains is designed to deal with the computational complexity and message exchange overhead problem caused by scale expansion of UDN. Finally, to further reduce the increasing computational complexity, message exchange overhead, and time complexity caused by scale expansion of UDN, this paper constructs a neighbor graph based on the mutual bias influence among cells, develops a graph-coloring-based clustering algorithm to classify cells into groups, and proposes a central-aided distributed CRE bias adjusting algorithm to obtain the optimal solution to the rate-related utility optimization problem based on local information. In the central-aided distributed CRE bias adjusting algorithm, a central macrocell is used to collect the information from the small cells, and the small cells distributively determine their CRE bias based on shared central information. The optimality and complexity of the proposed algorithms are proven and analyzed. Numerical results show that, compared with existing schemes, the proposed Gibbs-sampling-based algorithms can achieve a larger utility function with less iteration time.

EICIC Configuration Algorithm with Service Scalability in Heterogeneous Cellular Networks

Interference management is one of the most important issues in heterogeneous cellular networks with multiple macro and pico cells. The enhanced inter cell interference coordination (eICIC) has been proposed to protect downlink pico cell transmissions by mitigating interference from neighboring macro cells. Therefore, the adaptive eICIC configuration problem is critical, which adjusts the parameters including the ratio of almost blank subframes (ABS) and the bias of cell range expansion (RE). This problem is challenging especially for the scenario with multiple coexisting network services, since different services have different user scheduling strategies and different evaluation metrics. By using a general service model, we formulate the eICIC configuration problem with multiple coexisting services as a general form consensus problem with regularization and solve the problem by proposing an efficient optimization algorithm based on the alternating direction method of multipliers. In particular, we perform local RE bias adaptation at service layer, local ABS ratio adaptation at BS layer, and coordination among local solutions for a global solution at a network layer. To provide the service scalability, we encapsulate the service details into the local RE bias adaptation subproblem, which is isolated from the other parts of the algorithm, and we also introduce some implementation examples of the subproblem for different services. The extensive simulation results demonstrate the efficiency of the proposed algorithm and verify the convergence property.

A Markov Based Performance Analysis of Handover and Load Balancing in HetNets

LTE heterogeneous networks (HetNets) is becoming a popular topic since it was first developed in 3GPP Release 10. HetNets has the advantage to assemble various cell networks and enhance users’ Quality of Service (QoS) within the system. However, its development is still constrained by two main issues: 1) Load imbalance caused by different transmission powers for various tiers, and 2) The unbalanced transmission power may also increase unnecessary handover rate. In order to solve the first issue, Cell range expansion (CRE) can be applied in the system, which will benefit lower-tier cell during user association phase; CRE, Hysteresis Margin (HM) and Time-to-Trigger (TTT) will be utilized to bound UE within lower tier network of HetNets and therefore solve the second issue. On the other hand, the relationship of these parameters may be complicated and even reduce QoS if they are chosen incorrectly. This paper will evaluate the advantage and disadvantage of all three parameters and propose a Markov Chain Process (MCP) based method to find optimal HM, CRE and TTT values. And then, the simulation is taken and the optimal combination for our scenario is obtained to be 1 dB, 6 dB and 60 ms respectively. First contribution of this paper is to map the HetNets handover process into MCP and all the phases of handover can be calculated and analysed in probability way, so that further prediction and simulation can be realised. Second contribution is to establish a mathematical method to model the relationship of HM, CRE and TTT in HetNets, therefore the coordination of these three important parameters is achieved to obtain system optimization.

A Practical Tessellation-Based Approach for Optimizing Cell-Specific Bias Values in LTE-A Heterogeneous Cellular Networks

In order to implement an optimized solution for cell range expansion (CRE) and enhanced intercell interference coordination (eICIC) schemes in long-term evolution-advanced (LTE-A) heterogeneous cellular networks (HCNs) and to realize good load-balancing performance in existing LTE-A systems, a practical tessellation-based algorithm is proposed. In this algorithm, a globalized cell-specific bias optimization and a localized almost blank subframe (ABS) ratio update are proposed. The proposed scheme does not require major changes to existing protocols. Thus, it can be implemented in existing LTE-A systems with any legacy user equipment (UE) with only a partial update to the BSs and core networks. From simulation results, it is shown that the tessellation formed by the proposed approach is quite consistent with the optimal one for various realistic scenarios. Thus, the proposed scheme can provide a much better load-balancing capability compared with the conventional common bias scheme. Owing to the improved load-balancing capability, the user rate distribution of the proposed scheme is much better than that obtained from the conventional scheme and is even indistinguishable from that of the ideal joint user association scheme.

Energy Efficiency Analysis of Heterogeneous Cellular Networks With Extra Cell Range Expansion

The split control and user plane is key to the future heterogeneous cellular network (HCN), where the small cells are dedicated for the most data transmission while the macrocells are mainly responsible for the control signaling. Adapting to this technology, we propose a general and tractable framework of extra cell range expansion (CRE) by introducing an additional bias factor to enlarge the range of small cells flexibly for the extra offloaded macrousers in a two-tier HCN, where the macrocell and small cell users have different required data rates. Using stochastic geometry, we analyze the energy efficiency (EE) of the extra CRE with joint low power transmission and resource partitioning, where the coverages of EE and data rate are formulated theoretically. Numerical simulations verify that the proposed extra CRE can improve the EE performance of HCN, and also show that deploying more small cells can provide benefits for EE coverage, but the EE improvement becomes saturated if the small cell density exceeds a threshold. Instead of establishing the detail configuration, this paper can provide some valuable insights and guidelines to the practical design of future networks, especially for the traffic offloading in HCN.

SON Coordination in Heterogeneous Networks: A Reinforcement Learning Framework

An important problem of today’s mobile network operators is to bring down the capital expenditures and operational expenditures. One strategy is to automate the parameter tuning on the small cells through the so-called self-organizing network (SON) functionalities, such as cell range expansion, mobility robustness optimization, or enhanced Inter-Cell Interference Coordination. Having several of these functionalities in the network will surely create conflicts, as, for example, they may try to change the same parameter in the opposite directions. This raises that the need for an SON COordinator (SONCO) meant to arbitrate the parameter change requests of the SON functions, ensuring some degree of fairness. It is difficult to anticipate the impact of accepting several simultaneous requests. In this paper, we provide a SONCO design based on reinforcement learning (RL) as it allows us to learn from previous experiences and improve our future decisions. Typically, RL algorithms are complex. To reduce this complexity, we employ two flavors of function approximation and provide a study-case. Results show that the proposed SONCO design is capable of biasing this fairness among the SON functions by means of weights attributed to the SON functions. Also, we evaluate the tracking capability of the algorithms.

Coverage Performance Analysis of FeICIC Low-Power Subframes

Although the almost blank subframes (ABSFs) proposed in heterogeneous cellular networks can enhance the performance of the cell range expansion (CRE) user equipments (UEs), it significantly degrades the macro-cell total throughput. To address this problem, the low power subframes (LPSFs) are encouraged to be applied in the macro-cell center region by the further-enhanced inter-cell interference coordination. However, the residual power of the LPSF, which interferes with the CRE UEs, and the proportion of the LPSF affect the downlink throughput together. To achieve a better rate coverage probability, the appropriate LPSF power and the proportion are required. In this paper, the analytical results of the overall signal to interference and noise ratio coverage probability and the rate coverage probability are derived under the stochastic geometric framework. The optimal region bias ranges for maximizing the rate coverage probability are also analyzed. The results show that the ABSF still outperform the LPSF in terms of rate with the optimal range expansion bias, but lead to a heavier burden on the backhaul of the pico-cell. However, with a static range expansion bias, the LPSF provide better rate coverage than the ABSF. In addition, in a low-range expansion scenario, the reduced power of the LPSF has negligible effect on the rate coverage with the optimal resource partitioning.