Fractional Frequency Reuse Method Research Articles

Further Research on Frequency Allocation (19-Cell System) Method based on IFR and FFR

Many of the most advanced technology has a basic need for efficient telecommunication. In order to achieve this goal, the team should allocate those frequency channels in an intelligent way so that the interference can be reduced to the maximum extent. Here the team introduced a new method based on IFR3&IFR1 (Integer frequency reuse) in a 19-cell network, but also apply the FFR (fractional frequency reuse) method to reduce the interference ulteriorly. In the pure IFR situation, the integer frequency reuse factor and the cellular network specification collectively decide the network capacity. While in FFR only a fraction of the whole bandwidth is used by the users in the edge. By contrast, the users near the BS can make use of the total bandwidth. The cell is divided into an outer and an inner part in this effective way. Fractional Frequency Reuse (FFR) and its derivative method are accepted widely in the downlink (DL) inter-cell interference coordination(ICIC) schemes. The team also optimized the FFR method by measuring the distance in a more precise way. The team utilized Matlab to make a simulation of the system applying the new method and come to a couple of reasonable conclusions by comparing the FFR+IFR3 with FFR+IFR3. FFR+IFR3 has a better performance against FFR+IFR1 in a system whose distance between each cell is with more accuracy. While the average number of users per cell and transmission power for cell edge have little impact on average capacity. When the SNR increases, the network capacity starts steep but later flattens. Our method is more intelligent and can minish interference efficiently.

Comparison of FFR+IFR and IFR Models with Different Frequency Reuse Factors in Cellular Networks

With the development of information network transmission, how to efficiently complete frequency reuse has been studied by many scholars. Frequency reuse refers to reusing the same frequency in a digital cellular system. Generally, limited frequencies are divided into several groups. As we all know, fractional frequency reuse (FFR) and integer frequency reuse (IFR) are classical frequency reuse methods in cellular networks. The combination of FFR method and IFR method to find the best model has attracted the attention of researchers at home and abroad. Therefore, through the fusion and combination of the four models, this paper will first introduce two frequency reuse methods, IFR and FFR, as well as the combination of these two methods and the calculation methods of these two methods. Through Matlab software modeling and simulation, according to the average capacity results, study the impact of different user numbers on the average capacity of the central area and the edge area. The experimental results provide a new idea for future practical applications.

An Approach to Reduce Interference Using FFR in Heterogeneous Network

As the world is progressing towards 5G technology, its primary requirement is high throughput, low latency, high spectrum and energy efficiency and guaranteed QoS. High throughput is achievable when the user (UE) and the base station/Macro eNodeB (MeNB) are close to each other. This is achieved by using femtocell or Home eNodeB (HeNB). It is a kind of small cell. The femtocell needs to exist along with macrocell. Hence, they will share the resource along with the macrocell. There arises serious inter-channel and intra-channel interference (ICIC). To mitigate the interference, various solution methodologies, e.g. power control, co-operative communication and absolute blank sub-frame, can be used. In this research work, fractional frequency reuse method is discussed where the cell is segregated into centred and edge regions. All the centred, i.e. inner, regions can be assigned with the same frequency sub-band. Edge regions, i.e. outer region, can be assigned with different frequency sub-band with reuse factor of three. In this technique, ICIC can be reduced significantly. Hence, QoS can be improved and throughput of the system can also be enhanced. The outage probability can be reduced since cell-edge users are assigned with different sub-bands with high power.

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

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

Energy- and Spectral-Efficient Resource Allocation Algorithm for Heterogeneous Networks

In this paper, the tradeoff between energy efficiency and spectral efficiency in multicell heterogeneous networks is investigated. Our objective is to maximize both energy efficiency and spectral efficiency of the network, while satisfying the minimum rate requirements of the users. We define our objective function as the weighted summation of energy efficiency and spectral efficiency functions. The fractional frequency reuse (FFR) scheme is employed to suppress intercell interference. We formulate the problem as cell-center boundary selection for FFR, frequency assignment to users, and power allocation. The optimal solution of this problem requires exhaustive search over all cell-center radii, frequency assignments, and power levels. We propose a three-stage algorithm and apply it consecutively until convergence. First, we select the cell-center radius for the FFR method. Second, we assign the frequency resources to users to satisfy their rate requirements and also maximize the objective function. Third, we solve the power allocation subproblem by using the Levenberg-Marquardt method. Minimum rate requirements of users are also included in the solution by using dual decomposition techniques. Our numerical results show a Pareto-optimal solution for energy efficiency and spectral efficiency. We present energy efficiency, spectral efficiency, outage probability, and average transmit power results for different minimum rate constraints. Among other results, we show that, in a particular setting, 13% energy efficiency increase can be obtained in a multicell heterogeneous wireless network by sacrificing 7% spectral efficiency.

Improving spectrum efficiency in self-organized femtocells using learning automata and fractional frequency reuse

Deploying heterogeneous networks (HetNets) and especially femtocell technology improves indoor cell coverage and network capacity. However, since users install femtocells which usually reuse the same frequency band as macrocells, interference management is considered a main challenge. Recently, fractional frequency reuse (FFR) has been considered as a way to mitigate the interference in traditional as well as heterogeneous cellular networks. In conventional FFR methods, radio resources are allocated to macrocell/femtocell users only according to their region of presence ignoring the density of users in defined areas inside a cell. However, regarding the unpredictability of cellular traffic, especially on the femtocell level, smart methods are needed to allocate radio resources to the femtocells not only based on FFR rules, but also traffic load. In order to solve this problem, new distributed resource allocation methods are proposed which are based on learning automata (LA) and consider two levels of resource granularity (subband and mini-subband). Using the proposed methods, femto access points learn to choose appropriate subband and mini-subbands autonomously, regarding their resource requirements and the feedback of their users. The goal of the proposed methods is reduction of interference and improvement of spectral efficiency. Simulation results demonstrate higher spectral efficiency and lower outage probability compared to traditional methods in both fixed and dynamic network environments.

A Simple yet Effective Approach for Interference Mitigation in Tridimensional Two-Tier Femtocell Networks

Dense femtocell deployment in macrocell system is an important tendency in future cellular networks due to the increasing demand in indoor communications, where the cross-tier interference mitigation between the macrocell and femtocells is one of the most critical issues. However, the current studies mostly focus on the cross-tier interference in two-dimensional scenarios with a few works considering the tridimensional cell. In this paper, based on the traditional fractional frequency reuse (FFR) method, we propose a simple yet effective tridimensional frequency reuse strategy to mitigate the cross-tier interference in two-tier femtocell networks. We analyze the performance of the proposed strategy and present the theoretical expression of the interference and the data rate. Moreover, we compare it with the traditional FFR method and the original co-channel method. Simulation results show the huge gain achieved by our proposed strategy and demonstrate its effectiveness on interference mitigation in the tridimensional cell.

Deployment of Resource Allocation and Power Control Schemes in Long Term Evolution Advanced (LTE-A) Hybrid Network

Long Term Evolution Advanced (LTE-A) Hybrid network integrates Femtocell and Macrocell networks to obtain better coverage and improved capacity. One of the limiting factors faced by Hybrid network is Inter-Cell Interference (ICI). One way to get rid of the ICI is through Inter-Cell Interference coordination technique. In the last few years, interference coordination such as Fractional Frequency Reuse (FFR) technique is considered as the utmost important research topic in LTE cellular technology. This paper revisited FFR method and deployed Dynamic Femtocell Resource Allocation (DFRA) scheme to ensure the resources assigned to Femtocells are mutually exclusive with adjacent Macrousers or adjacent Femtocells. Furthermore, in the scenario of high density Femtocells (when orthogonal resource exhausted), the power control schemes such as Power based Femtocell Base Station Power Control (PPC), SINR based Femtocell Base Station Power Control (SPC) and SINR based Neighboring Femtocell Power Control (SNPC) are integrated into the system. The deployment of the schemes has augmented the performance of the network and shows increment of 11.43% supported active users with an average data rate inclined by 22.19 Mbps.

분할대역 중첩을 통한 부분 주파수 재사용의 성능 향상

In OFDMA-based cellular system, inter-cell interference (ICI) reduces system capacity by aggravating receiving performance of the users located in edge of the cell. Therefore, to mitigate ICI is very important issue in cellular system. To deal with ICI problem, fractional frequency reuse (FFR) is introduced. FFR is an interference management technique. It separates each cell into inner cell and outer cell. Then, it allocates whole system bandwidth to inner cell and different frequency partition to each sector of outer cell. By doing this, outer cell users can ignore interferences from adjacent cells. So, the receiving performance of the cell edge users can be fairly increased. However, using FFR technique has a fatal side effect. In order to use different frequency partition among three sectors of outer cell, they can use only a third of the whole system bandwidth. Then, the reduction of available bandwidth reduces the system throughput directly. To solve this problem, we propose a new FFR method that allocates partially overlapped frequency partition to each sector of outer cell. And then, we suggest a proper overlapping ratio for practical cellular system.