Joint Optimization of The two Tier Femto cells and Macro cell Users OFDMA Network (original) (raw)
Related papers
Resource allocation in spectrum-sharing ofdma femtocells with heterogeneous services
Femtocells are being considered a promising technique to improve the capacity and coverage for indoor wireless users. However, the cross-tier interference in the spectrum-sharing deployment of femtocells can degrade the system performance seriously. The resource allocation problem in both the uplink and the downlink for two-tier networks comprising spectrum-sharing femtocells and macrocells is investigated. A resource allocation scheme for cochannel femtocells is proposed, aiming to maximize the capacity for both delay-sensitive users and delay-tolerant users subject to the delay-sensitive users' quality-of-service constraint and an interference constraint imposed by the macrocell. The subchannel and power allocation problem is modeled as a mixed-integer programming problem, and then, it is transformed into a convex optimization problem by relaxing subchannel sharing; finally, it is solved by the dual decomposition method. Subsequently, an iterative subchannel and power allocation algorithm considering heterogeneous services and cross-tier interference is proposed for the problem using the subgradient update. A practical low-complexity distributed subchannel and power allocation algorithm is developed to reduce the computational cost. The complexity of the proposed algorithms is analyzed, and the effectiveness of the proposed algorithms is verified by simulations.
Fair Resource Allocation for OFDMA Femtocell Networks With Macrocell Protection
IEEE Transactions on Vehicular Technology, 2000
We consider the joint subchannel allocation and power control problem for OFDMA femtocell networks in this paper. Specifically, we are interested in the fair resource sharing solution for users in each femtocell that maximizes the total minimum spectral efficiency of all femtocells subject to protection constraints for the prioritized macro users. Toward this end, we present the mathematical formulation for the uplink resource allocation problem and propose an optimal exhaustive search algorithm. Given the exponential complexity of the optimal algorithm, we develop a distributed and low-complexity algorithm to find an efficient solution for the problem. We prove that the proposed algorithm converges and analyze its complexity. Then, we extend the proposed algorithm in three different directions, namely downlink context; resource allocation with rate adaption for femto users; and consideration of a hybrid access strategy where some macro users are allowed to connect with nearby femto base stations to improve the performance of the femto tier. Finally, numerical results are presented to demonstrate the desirable performance of the proposed algorithms.
Energy Efficient Resource Allocation in Two-Tier OFDMA Networks with QoS Guarantees
Wireless Networks, 2017
In this paper, we study joint power and subchannel allocation problem for OFDMA based femtocell networks with focus on uplink direction. We minimize the aggregate power of all Femto user equipments and maximize the total system energy efficiency while satisfying the minimum required rate of all users. An interference limit constraint is considered to protect the QoS of macrocells. The original problem is a mixed-integer non-convex optimization problem which is converted to a convex problem using the time-sharing concept. Three algorithms are proposed to provide a scheme to optimize the goal function while meeting the constraints. The complexity order of all algorithms was investigated and was compared to other alternative solutions. The analytic and simulation results have demonstrated that the proposed algorithms could achieve significant power saving and better energy efficiency compared to existing algorithms.
In this paper, we consider the joint subchannel and power allocation problem in both the uplink and the downlink for two-tier networks comprising spectrum-sharing macrocells and femtocells. A joint subchannel and power allocation scheme for co-channel femtocells is proposed, aiming to maximize the capacity for delay-tolerant users subject to delay-sensitive users' quality of service and interference constraints imposed by macrocells. The joint subchannel and power allocation problem is modeled as an mixed integer programming problem, then transformed into a convex optimization problem by relaxing subchannel sharing, and finally solved by a dual decomposition approach. The effectiveness of the proposed approach is verified by simulations and compared with existing scheme.
Power Minimization Based Resource Allocation for Interference Mitigation in OFDMA Femtocell Networks
IEEE Journal on Selected Areas in Communications, 2000
With the introduction of femtocells, cellular networks are moving from the conventional centralized network architecture to a distributed one, where each network cell should make its own radio resource allocation decisions, while providing inter-cell interference mitigation. However, realizing such distributed network architecture is not a trivial task. In this paper, we first introduce a simple self-organization rule, based on minimizing cell transmit power, following which a distributed cellular network is able to converge into an efficient resource reuse pattern. Based on such self-organization rule and taking realistic resource allocation constraints into account, we also propose two novel resource allocation algorithms, being autonomous and coordinated, respectively. Performance of the proposed self-organization rule and resource allocation algorithms are evaluated using system-level simulations, and show that power efficiency is not necessarily in conflict with capacity improvements at the network level. The proposed resource allocation algorithms provide significant performance improvements in terms of user outages and network capacity over cutting-edge resource allocation algorithms proposed in the literature.
IET Communications, 2016
This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macrocells and femtocells sharing the same frequency band. The focus is to devise optimised policies for femtocells' access to the shared spectrum, in terms of femtocell transmissions, in order to maximise femto users sum data rate while ensuring that certain level of quality of service (QoS) for the macro-cell users in the vicinity of femtocells is provided. The optimal solution to this problem is obtained by employing the well-known Dual Lagrangian method and the optimal femtocell transmit power and resource allocation solution is derived in detail. However, the optimal solution introduces high computational complexity and may not be feasible to apply in real-time systems. To this end, we propose a heuristic solution to the problem. The algorithms to implement both optimal and efficient suboptimal schemes in a practical system are also given in detail while their complexity is compared. Simulation results show that our proposed dynamic resource allocation scheme a) ensures the macro users QoS requirements compared to the Reuse-1 scheme, where femtocells are allowed to transmit at full power and bandwidth; b) can maintain femto user data rates at high levels, compared to the Orthogonal Frequency Reuse scheme, where the network bandwidth resources are partially divided amongst macro and femtocells; and c) provides performance close to the optimal solution, while introducing much lower complexity.
Interference-aware resource allocation in co-channel deployment of OFDMA femtocells
2012
Macrocells may suffer serious uplink interference introduced by the deployment of co-channel femtocells. In this paper, an interference-aware pricing-based resource allocation algorithm for co-channel femtocells is proposed to alleviate their interference to macrocells without degrading the femtocell's capacity. The subchannel and power allocation problem is modeled as a non-cooperative game. A suboptimal subchannel allocation algorithm and an optimal power allocation algorithm are proposed to implement the resource allocation game. Simulation results show that the proposed algorithm not only improves the capacity of the macrocell but also the total capacity of the two-tier network, as compared with the unpriced subchannel allocation and Modified Iterative Water Filling (MIWF) power allocation algorithm.
2010
For an orthogonal frequency division multiple access (OFDMA) downlink of a spectrally coexisting macro and femto network, a resource allocation scheme would aim to maximize the area spectral efficiency (ASE) subject to constraints on the radio resources per transmission interval accessible by each femtocell. An optimal resource allocation scheme for completely decentralized deployments leads however to a nonconvex optimization problem. In this paper, a filled function method is employed to find the global maximum of the optimization problem. Simulation results show that our proposed method is efficient and effective.
Radio resource allocation in OFDMA multi-cell networks
2010
In this paper, the problem of allocating users to radio resources (i.e., subcarriers) in the downlink of an OFDMA cellular network is addressed. We consider a multi-cellular environment with a realistic interference model and a margin adaptive approach, i.e., we aim at minimizing total transmission power while maintaining a certain given rate for each user. The computational complexity issues of the resulting model is discussed and proving that the problem is NP-hard in the strong sense. Heuristic approaches, based on network flow models, that finds optima under suitable conditions, or "reasonably good" solutions in the general case are presented. Computational experiences show that, in a comparison with a commercial state-of-the-art optimization solver, the proposed algorithms are effective in terms of solution quality and CPU times.
2014 IEEE 22nd International Symposium of Quality of Service (IWQoS), 2014
Recently, LTE-based femtocell system has received significant attention as a promising solution offering high-speed services, enhanced indoor coverage and increased system capacity. Intelligently allocate resources in multiuser OFDMAbased network is the substantial aim towards interference mitigation and enhancing power and spectral efficiencies. In this paper, we propose a downlink joint resource allocation with Adaptive Modulation and Coding (AMC) technique for such system, namely AMC-QRAP. The proposal core is adjusting the transmission link to the channel status and users demand through the power control and suitable selection of the modulation/coding scheme. Clustered network is adopted and users differentiation is considered providing Quality of Service (QoS) in the network. Our resolution model is solved as an optimization problem using the linear programming. We show through extensive simulations the outperformance of our method compare to different state-ofthe-art methods using different evaluation metrics.