- Research
- Open Access
Fairness guaranteed novel eICIC technology for capacity enhancement in multi-tier heterogeneous cellular networks
- Qixun Zhang^{1}Email author,
- Tuo Yang^{1},
- Yue Zhang^{1} and
- Zhiyong Feng^{1}
https://doi.org/10.1186/s13638-015-0300-y
© Zhang et al.; licensee Springer. 2015
- Received: 1 November 2014
- Accepted: 16 February 2015
- Published: 10 March 2015
Abstract
Driven by surging demands for high data rate services and better user experiences, there is an increasing capacity demand in heterogeneous cellular networks. As one of the promising solutions for capacity enhancement, densely deployed small cells are proposed to provide a huge capacity gain and improve the user experience with high data rate services. However, the inter-cell interference among densely deployed cells is a big challenge that constraints the performance of capacity improvements in hierarchical multi-tier heterogeneous cellular networks. To minimize the inter-cell interference and achieve a fairness guaranteed solution among different users, a novel enhanced inter-cell interference coordination (eICIC) technology is proposed by jointly considering about the cell range expansion (CRE) scheme to minimize interferences among multi-tier cellular networks, improving the network throughput and quality of service (QoS). Optimal CRE bias and almost blank subframe (ABS) ratio solutions are achieved in this paper by considering the fairness among users at the center and cell edge. Moreover, the multi-objective decision-making problem is solved by maximizing the proportional fairness (PF) utility and area capacity in multi-tier heterogeneous cellular networks. Simulation results denote that a tradeoff between fairness and network throughput is achieved when CRE bias is from 8 to 12 dB and ABS ratio is from 4/8 to 6/8.
Keywords
- Heterogeneous cellular networks
- Small cell
- CRE
- eICIC
- Multi-objective decision-making problem
1 Introduction
Recently, the rapid developments on various applications and different service demands in cellular networks lead to the exponentially surge on mobile traffics. According to statistics, the mobile traffic will grow up to 1,000 times (1,000 ×) in the next 10 years. Moreover, the user data rate will also increase from approximately 1 Mbit/s today to at least 10 Mbit/s over the next decade in [1]. However, the explosion of mobile traffics brings in both new opportunities and challenges for the cellular network optimization for operators. In general, there are three ways to enhance the network capacity, such as the spatial densely deployment, spectral aggregation, and spectrum efficiency improvement. Spatial densely deployment is realized by deploying multi-tier overlayed heterogeneous networks (HetNets) to improve the network capacity and ensure the cell coverage in [2]. Spectral aggregation refers to the utilization of carrier aggregation (CA) technology to support a wide system bandwidth up to 100 MHz in [3]. In terms of the spectrum efficiency, it can be improved by introducing new transmission technologies such as cooperative multipoint (CoMP) in [4]. Among these technologies, HetNet is the most effective and low-cost solution to improve the capacity in [5,6] by deploying small cells within multi-tier heterogeneous cellular networks.
In the multi-tier HetNet scenario, low-power small cells, such as femto, pico, and relay nodes, are overlaid within the coverage of macrocells, which are placed in an unplanned manner in [7]. Compared with macrocell, small cells have much lower transmit power, smaller coverage, and lower cost which are easy to maintain and deploy. Small cells can alleviate the traffic pressure of macrocell network by offloading part of the traffic to them. However, HetNet will face a series of problems as well, which will affect the capacity enhancement of multi-tier heterogeneous cellular networks. In [8], some cooperative distributed radio resource management algorithms for time synchronization, carrier selection, and power control were discussed for hyper-dense small cell deployment. Among these challenges of hyper-dense HetNet, traffic imbalance and inter-cell interference among multiple cells are two tough problems which lead to the inefficient radio resource utilization and affect the capacity and sum data rate of HetNet in [9].
To solve these problems, both cell range expansion (CRE) and enhanced inter-cell interference coordination (eICIC) technologies were proposed to improve the network capacity of HetNet in the 3GPP Release 8 and Release 9. If adopt the maximum reference signal received power (RSRP) access scheme, only a few users can be associated with low power nodes, which will cause the load imbalance among cells in HetNets and greatly reduce the capacity gain from small cell deployment. Therefore, a positive bias value is added to the RSRP of user equipments (UE) by using the CRE technology in [10], which can offload part of macrocell UE (MUE) to small cells and reduce the uplink interference among multi-tier networks. However, small cells serving the range expanded UEs with a low value of signal to interference plus noise ratio (SINR) will surfer serious downlink interference from macrocells, which is a critical problem unsolved yet.
In terms of the eICIC technology, it can efficiently improve the range expanded UEs’ performance and reduce the inter-cell interference among cells in multi-tier heterogeneous cellular networks. As a time-domain interference coordination scheme, the eICIC technology divides the time frames into almost blank subframes (ABS) and normal subframes in [11]. And MUEs and range expanded UEs are scheduled on normal subframes and ABSs orthogonally, which can relieve the interference from macrocells to the range expanded UEs and improve the quality of service (QoS). But the eICIC technology reduces the time resources of MUEs for communication at the same time.
In the literature, the joint usage of CRE and eICIC is proved to be an effective solution on improving the system throughput of HetNet in [12,13], but it is much more complicated for mathematical analysis of network capacity. Besides, if a larger CRE bias of RSRP is applied to reduce the load imbalance among different cells by the traffic offloading technology, more ABSs are needed in order to guarantee the performance of range expanded UEs. Therefore, the CRE bias and ABS muting ratio are key parameters that should be configured appropriately to ensure the performance on the interference mitigation and the network capacity enhancement using the joint CRE and eICIC schemes. In [14], a joint optimization of the CRE bias and radio resources is discussed to ensure the performance of picocells. However, the over-the-air signaling has not been considered yet which leads to the numerical optimization, and investigation results are unpractical. Moreover, the performance of CRE and eICIC schemes is studied and evaluated by system simulation results in [15], which lacks the mathematical analysis and does not consider about the configuration of CRE and eICIC. Furthermore, the analytical approaches for CRE biasing and eICIC are studied in [16-20]. The SINR of HetNet with cell association is studied in [16], but it does not include the resource partitioning scheme and only analyzes the SINR. And the SINR and mean throughput-based analysis for resource partitioning are analyzed in [17,18], without considering the user association effect. Optimal CRE bias and ABS ratio scheme are proposed in [19] based on the average per user spectral efficiency. In [20], the joint analysis of resource partitioning and offloading scheme is proposed in terms of the metrics of the effective distribution of SINR but has no consideration about the optimal parameter configuration effects on UE’s fairness. Considering fairness, a graph-based distributed algorithm called fairness guaranteed cooperative resource allocation (FGCRA) is proposed to manage the interference among femtocells in [21], but it only considers the sub-channel allocation which has not considered about the time resource.
Considering the disadvantages of existing works and problems unsolved, a novel eICIC technology is proposed by jointly considering the CRE scheme to minimize interferences among multi-tier cellular networks in this paper, improving the network throughput and QoS and guarantee the fairness of users meanwhile. Both the poisson point process (PPP) model and two metrics of capacity performance are used including the average capacity per cell and the average capacity per area unit. Optimal CRE bias and ABS ratio are achieved by taking into account the fairness effect of users at the center and cell edge. Furthermore, the multi-objective decision-making problem is solved to maximize the proportional fairness (PF) utility [22] and area capacity of multi-tier heterogeneous cellular networks. Simulations are performed to evaluate the performance of proposed technology in this paper. The tradeoff between fairness and network throughput is achieved in this paper, when the CRE bias is from 8 to 12 dB and ABS ratio is from 4/8 to 6/8.
The remainder of this paper is organized as follows. Both the system model and problem formulation of heterogeneous cellular networks are proposed in Section 1. The optimal solution of joint CRE bias and ABS ratio technology is proposed in Section 1 by considering about the fairness effect among UEs. Results are discussed and analyzed thoroughly in Section 1. Finally, a brief conclusion is described in Section 1.
2 System model and problem formulation
A typical scenario of one macrocell overlapped by small cells, such as the picocells, is described in detail in this section. Besides, the problem formulations of downlink capacity and interference are proposed by taking into account the macrocells and small cells in multi-tier heterogeneous cellular networks.
2.1 System model and scenario
2.2 Problem formulation
In multi-tier heterogeneous cellular networks, the positions of base stations (BSs) are denoted by Φ _{ k } in the kth tier which follows a homogeneous poisson point process (PPP) distribution with a intensity of λ _{ k }. In our discussion, the first tier (k=1) represents macrocells and the second tier (k=2) represents picocells. Moreover, the positions of UEs are depicted by Φ _{ u } which follows a homogeneous PPP distribution with a intensity of λ _{ u } and is independent of Φ _{ k }. The transmit power of each BS is assumed as the same and denoted by P _{ k } with the bandwidth of W. And the path loss ratio is {α _{ k }}=4. Assumed that the multi-tier heterogeneous cellular network is an interference limited system, the inter-cell interference is dominant and the background noise is ignored for analysis simplicity in this paper.
2.2.1 Cell association using CRE technology
In terms of different CRE bias values, UEs are divided into three types.
Type 1 U _{ 1 }: MUE associated to k=1 tier. The RSRP is correspond to P _{ r,1}>B P _{ r,2}.
Type 2 U _{ 2 }: PUE associated to k=2 tier at the center of picocell without CRE. The RSRP is correspond to P _{ r,1}<P _{ r,2}.
Type 3 U _{ cre }: Picocell UE using CRE (PUE _{cre}) associated to k=2 tier at the cell edge of picocell with CRE. The RSRP is correspond to P _{ r,2}<P _{ r,1}<B P _{ r,2}.
2.2.2 Resource partitioning using eICIC technology
To minimize the interference from macrocell to PUEs, the eICIC technology is utilized which is a time resource partitioning approach. The macrocell mutes its transmission on certain fraction of subframes, picocell schedule UEs in the range expanded regions on the corresponding subframes to avoid the interference from the macrocell. Furthermore, macrocell configures its ABS with the ratio β. Thus, the time resource ratio of MUE is ρ _{1}=1−β, the time resource ratio of PUE _{cre} is denoted by ρ _{cre}=β, and the time resource ratio of PUE that is not affected by ABS is denoted by ρ _{2}=1.
2.3 Capacity analysis using CRE and eICIC technologies
Thus, the proposed CRE bias scheme can realize the load balance among different cells and increase the capacity in multi-tier heterogeneous cellular networks with appropriate CRE bias value configuration. However, PUE _{cre} will suffer the strong interference from MBS in the vicinity. Furthermore, in order to minimize the inter-cell interference, the eICIC technology using ABS ratio configuration is applied to utilize both the temporal and spatial separations among MUEs and PUEs. But the system capacity of multi-tier heterogeneous cellular networks is affected in terms of the inefficient resource utilization. Thus, how to improve the capacity by considering the tradeoff between CRE bias B and ABS ratio β is a big challenge, which has not been solved yet. In summary, a novel eICIC technology by jointly utilizing CRE bias and ABS ratio scheme is proposed by considering the fairness aspect among different users in Section 1 to minimize the inter-cell interferences among multi-tier heterogeneous cellular networks, improving the network throughput and QoS.
3 Optimal CRE bias and ABS ratio solution based on fairness
In this section, an optimal CRE bias and ABS ratio scheme is proposed by considering the fairness aspect among different UEs in multi-tier heterogeneous cellular networks. CRE technology can offload part of MUEs into small cells, and the data rate of a single MUE will improve with the increase of CRE bias value B. Thus, the proposed CRE bias scheme can realize the load balance and increase the capacity in multi-tier heterogeneous cellular networks with an appropriate CRE bias value configuration. However, PUE _{cre} will suffer the strong inter-cell interference from MBS. To minimize the interference, ABS ratio configuration is applied as an eICIC scheme to utilize both the temporal and spatial separations among MUEs and PUEs with the capacity deteriorated. Thus, in order to improve the capacity in terms of the tradeoff between CRE bias B and ABS ratio β is considered as an effective solution to minimize the interference among cells, which is critical for network capacity enhancement in multi-tier heterogeneous cellular networks.
4 Results and analysis
In this section, numerical simulation is performed with different scenarios and results are analyzed thoroughly. Macrocells and picocells are deployed with densities of λ _{1}=4.62 and λ _{2}=K _{ P } λ _{1} BS/km ^{2}, respectively. And the transmit power for macrocell and picocell is P _{1}=46 and P _{2}=30 dBm. The system bandwidth is defined by W=10 MHz, and the path loss exponent is denoted by α=4.
4.1 Capacity analysis of stand-alone effects by BS density, CRE, and eICIC
Considering different parameters that affect the performance of system capacity in multi-tier heterogeneous cellular networks, key parameters, such as the BS density, CRE, and eICIC, are discussed with numerical results in terms of different ratios of PUE, system throughput of various cells.
4.2 Optimal CRE bias and ABS ratio technology
By utilizing the lexicographic method, the optimal CRE bias and ABS ratio are achieved in multi-tier heterogeneous cellular networks. In the case of picocell’s density λ _{2}=6λ _{2}, the PF utility has little difference when the CRE bias is from 8 to 12 dB and ABS ratio is from 3/8 to 6/8 as shown in Figure 7. In order to maximum the average capacity per cell, the optimal CRE bias is 12 dB and ABS ratio is 6/8. Similarly, when the picocell’s density λ _{2}=12λ _{2}, the optimal CRE bias is 10 dB and ABS ratio is 5/8. In addition, the optimal CRE bias and ABS ratio are less affected by picocell’s density. Therefore, simulation results show that when the CRE bias is from 8 to 12 dB and ABS ratio is from 4/8 to 6/8, the optimal solution is achieved which can improve the capacity by 40% in terms of the fairness among different UEs in multi-tier heterogeneous cellular networks.
4.3 LTE-A system-level simulation results of novel eICIC technology
Simulation parameters
Macrocell | Picocell | |
---|---|---|
Cellular layout | 19 cell sites, 3 sectors per site | 4 picocells per sector |
Number of UEs | 60 per macro cell | 60 per macro cell |
Distance-dependent path loss | ITU urban macro(UMa) [7] | ITU urban micro(UMi) [7] |
Shadowing standard deviation | 8 dB | 10 dB |
Penetration loss | 0 dB | 0 dB |
Total eNodeB Tx power | 46 dBm | 30 dBm |
Antenna configuration | 2 × 2 (uncorrelated) | 2 × 2 (uncorrelated) |
Antenna pattern | 3D | 2D |
Antenna height | 25 m | 10 m |
Antenna gain | 14 dBi | 5 dBi |
Carrier frequency | 2 GHz | 2 GHz |
System bandwidth | 10 MHz | 10 MHz |
Traffic model | Full buffer, full load | Full buffer, full load |
5 Conclusion
In this paper, the joint CRE and eICIC scheme is proposed to minimize the inter-cell interference in multi-tier heterogeneous cellular networks. And the optimal CRE bias and ABS ratio solutions are achieved by taking into account the fairness effect among different UEs. The multi-objective decision-making scheme is designed to maximize the PF utility and the aera capacity. Simulation results show that when the CRE bias is from 8 to 12 dB and ABS ratio is from 4/8 to 6/8, the optimal solution is achieved which can improve the capacity by 40%, which considers about the fairness among different UEs.
Declarations
Acknowledgements
This work was sponsored by the National Natural Science Foundation of China (61201152, 61227801), the National High-tech R&D Program (863 Program 2014AA01A707).
Authors’ Affiliations
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