Cluster based resource allocation in two‐tier HetNets with hierarchical throughput constraints

Two‐tier heterogeneous networks (HetNets), formed by deploying small cell base stations (SBSs) over existing macrocells, can enhance the network performance in future fifth generation network. However, the cross‐/co‐tier interference in HetNets also will severely influence the user throughput of both tiers. In this paper, we investigate the resource allocation and interference mitigation problem in cluster based orthogonal frequency division multiple access (OFDMA) two‐tier HetNets. In a typical cluster, one SBS is selected as the cluster head to allocate resources among all small cells to guarantee their throughput requirements. Hybrid access policy enables small cells to suppress the cross‐tier interference and earn additional revenue from macrocells, but it also leads to decrease of available resources for small cell users (SUs). To compensate hybrid access SBSs for their resources loss, we impose hierarchical SU throughput constraints on the optimization problem, which guarantee these small cells more resources than closed access ones. Besides, the cross‐tier interference constraint is also considered to protect the transmissions of macrocell users. Accordingly, a subgradient iteration based resource allocation algorithm is proposed. Numerical results show that the proposed algorithm can satisfy SU throughput constraints of all small cells with different access policies and guarantee quality of service requirements of all accessed macrocell users in hybrid access small cells.     

Distributed optimization of enhanced intercell interference coordination and resource allocation in heterogeneous networks

In two‐tier heterogeneous networks (HetNets), the cross‐tier interference caused by spectrum sharing between macrocell and small cells poses obstacle to ideal overall network performance. Both enhanced intercell interference coordination (eICIC) at the macrocell base station (MBS) and resource allocation (RA) at small cell base station (SBS) have been considered as efficient approaches to mitigate the cross‐tier interference. In this paper, we propose a distributed optimization framework to jointly optimize the eICIC and RA schemes at different tiers. In specific, an enhanced almost blank subframe (ABS) scheme is performed by the MBS to encourage SBSs to adopt hybrid access policy and admit the offloaded macrocell users (MUs) so as to guarantee their QoS requirements. To model the intricate interaction between two tiers, we formulate the joint optimization problem as a one‐leader multiple‐follower Stackelberg game. We prove the existence of Stackelberg equilibrium (SE) and obtain the optimal strategies for both tiers. Numerical results are presented to show that the proposed framework with hybrid access policy converges to a unique SE and utilities for both tiers is maximized, which creates a win‐win situation.     

Ant Colony Optimization Based Sub-channel Allocation Algorithm for Small Cell HetNets

Two-tier heterogeneous networks (HetNets) composed of a conventional macrocellular network and small cell networks (SCNs) have been proposed in the literature with the aim to extend indoor coverage and realize efficient radio resource usage. As SCN shares the same frequency band with the underlying macrocell, the cross tier interference needs to be mitigated since the inter-SCN and cross tier interference at the SCN boundary may result in undesirable network performance degradation. In this paper, we propose an intelligent physical resource block (PRB) allocation as a solution to mitigate the downlink intra-SCN interference as well as the inter-tier interference in OFDM-based systems. The allocation of the PRBs to the network users is formulated as a graph coloring problem, and solved using an ant colony optimization (ACO)-based approach. Simulation results are provided, showing that our ACO-based algorithm outperforms the Received Power-based Allocation (RPA) and Received SINR-based Allocation (RSA) algorithms in terms of average SINR experienced by network users, outage probability, and number of required PRBs.     

Price‐based interference management in dense femtocell systems

Femtocell technology has been drawing considerable attention as a cost‐effective means of improving cellular coverage and capacity. However, under co‐channel deployment, femtocell system in dense environment may incur high uplink interference to existing macrocells and experiences strong inter‐cell interference at the same time. To manage the uplink interference to macrocell, as well as the inter‐cell interference, this paper proposes a price‐based uplink interference management scheme for dense femtocell systems. Specifically, on the one hand, to guarantee the macrocell users' quality of service, the macrocell base station prices the interference from femtocell users (FUEs) subject to a maximum tolerable interference power constraint. On the other hand, the inter‐cell interference is also taken into consideration. Moreover, a Stackelberg game model is adopted to jointly study the utility maximization of the macrocell base station and FUEs. Then, in order to reduce the amount of information exchange, we design a distributed power allocation algorithm for FUEs. In addition, admission control is adopted to protect the active FUEs' performance. Numerical results show that the price‐based interference management scheme is effective. Meanwhile, it is shown that the distributed power allocation combined with admission control is capable of robustly protecting the performance of all the active FUEs. Copyright © 2013 John Wiley & Sons, Ltd.     

Stackelberg game for backhaul resource allocation in the two-tier LTE femtocell networks

As one promising technology for indoor coverage and service offloading from the conventional cellular networks, femtocells have attracted considerable attention in recent years. However, most of previous work are focused on resource allocation during the access period, and the backhaul involved resource allocation is seriously ignored. The authors studied the backhaul resource allocation in the wireless backhaul based two-tier heterogeneous networks （HetNets）, in which cross-tier interference control during access period is jointly considered. Assuming that the macrocell base station （MBS） protects itself from interference by pricing the backhaul spectrum allocated to femtocells, a Stackelberg game is formulated to work on the joint utility maximization of the macrocell and femtocells subject to a maximum interference tolerance at the MBS. The closed-form expressions of the optimal strategies are obtained to characterize the Stackelberg equilibriums for the proposed games, and a backhaul spectrum payment selection algorithm with guaranteed convergence is proposed to implement the backhaul resource allocation for femtocell base stations （FBSs）. Simulations are presented to demonstrate the Stackelberg equilibrium （SE） is obtained by the proposed algorithm and the proposed scheme is effective in backhaul resource allocation and macrocell protection in the spectrum-sharing HetNets.     

Dynamic Orthogonal Frequency Division Multiple Access resource management for downlink interference avoidance in two‐tier networks

In two‐tier networks, which consist of macrocells and femtocells, femtocells can offload the traffic from macrocells thereby improving indoor signal coverage. However, the dynamic deployment feature of femtocells may result in signal interference due to limited frequency spectrum. The tradeoff between broad signal coverage and increased signal interference deserves further exploration for practical network operation. In this paper, dynamic frequency resource management is proposed to avoid both co‐tier and cross‐tier Orthogonal Frequency Division Multiple Access downlink interference and increase frequency channel utilization under co‐channel deployment. A graph‐based non‐conflict group discovery algorithm is proposed to discover the disjoint interference‐free groups among femtocells in order to avoid the co‐tier interference. A macrocell uses the femtocell gateway for frequency resource allocation among femtocells to avoid cross‐tier interference. We formulate the optimized frequency resource assignment as a fractional knapsack problem and solve the problem by using a greedy method. The simulation results show that the average data transfer rate can be increased from 21% to 60%, whereas idle rate and blocking rate are decreased in the range of and , respectively, as compared with conventional graph coloring and graph‐based dynamic frequency reuse schemes. Copyright © 2013 John Wiley & Sons, Ltd.     

Energy‐efficient resource allocation for device‐to‐device communication through noncooperative game theory

Wireless network with high data rate applications has seen a rapid growth in recent years. This improved quality of service (QoS) leads to huge energy consumption in wireless network. Therefore, in order to have an energy‐efficient resource allocation in cellular system, a device‐to‐device (D2D) communication is the key component to improve the QoS. In this paper, we propose a noncooperative game (NCG) theory approach for resource allocation to improve energy efficiency (EE) of D2D pair. A three‐tier network with macrocell base station (MBS), femtocell base station (FBS), and D2D pair is considered, which shares the uplink resource block. A resource allocation strategy with constraints is arrived, which maintains minimum throughput for each user in the network. The proposed resource allocation strategy optimizes the EE of D2D pair in the three‐tier network, which achieves Nash equilibrium (NE) and Pareto optimality (PO). Simulation results validate that EE is uniform and optimum for all D2D pair, which converges to NE when channel is static and it converges to PO when the channel is dynamic.     

An efficient interference mitigation approach via quasi‐access in two‐tier macro‐femto heterogeneous networks

Two‐tier heterogeneous networks, where the current cellular networks, that is, macrocells, are overlapped with a large number of randomly distributed femtocells, can potentially bring significant benefits to spectral utilization and system capacity. In a two‐tier network, the cross‐tier interference needs to be handled properly. Unlike the downlink interference, the uplink (UL) interference at femtocell caused by macrocell user equipment (MUE) has not been addressed sufficiently. When an MUE is located near the coverage of femtocell, its transmit power may cause UL interference to the femtocell receiver, especially for the closed subscriber group femtocells that share the entire frequency spectrum with macrocell. We propose a novel quasi‐access strategy, which allows the interfering MUE to connect with the interfered femtocell access point (FAP) while only via UL. It can significantly alleviate the UL interference at the FAP as well as its neighbors, in the meantime, benefit the macro‐tier. Copyright © 2013 John Wiley & Sons, Ltd.     

Pricing framework for almost blank subframe scheme in two‐tier heterogeneous networks

As a part of enhanced inter‐cell interference coordination (eICIC), almost blank subframe (ABS) is an efficient technique to mitigate the cross‐tier interference of two‐tier heterogeneous networks (HetNets) and enhance overall network performance. However, in small cells with closed subscriber group (CSG) mode, how to motivate small cell base stations (SBSs) to adopt ABS schemes is still one of technical challenges due to the selfish nature of SBSs. In this paper, we propose a pricing framework with ABS scheme that benefit both the macrocell and small cell tier. Within the proposed framework, each SBS with closed access policy performs ABS scheme by muting a portion of the whole frame in time domain, and then dedicating this interference‐free subframe to macrocell users (MUs) for exclusive use. In return, the macrocell base station (MBS) announces the price for these ABSs and offers a certain amount of revenue to each SBS according to the length of its ABS. Furthermore, we extend the small cell performance analysis to the scenario of hybrid access policy, which allow neighboring MUs to access small cells. To investigate the interaction between two tiers, we formulate the proposed framework as a one‐leader multiple‐follower Stackelberg game, which regards the MBS and SBSs as leader and followers, respectively. On the basis of the theoretical analysis, we prove that a unique Stackelberg equilibrium (SE) exists and obtain the optimal strategies for both tiers. Numerical results evaluate the utility performance of both tiers when SE is achieved and verify the validity of the proposed framework.     

LTE-A异构网络下的高效资源分配算法

分析了OFDMA上行系统中,由宏基站(macrocell)和家庭式基站(femtocell)组成的双层网络,并提出了高效的资源分配算法。为避免严重的跨层干扰导致双层网络中的资源分配不协调,提出了一个跨层干扰控制算法。在基于干扰控制算法的结果上,提出包括功率分配和频谱分配的资源分配算法,以满足UE的目标速率,并获得较好的吞吐量性能。通过仿真,结果显示所提的资源分配算法相比较传统的算法,尤其在UE QoS保证和吞吐量性能的体现上,能获得明显的性能增益。     

分层异构网络中基于斯坦克尔伯格博弈的资源分配算法

分层异构网络中家庭基站与宏基站之间往往存在干扰,如何分配资源以获得高谱率和高容量、保证用户性能一直是研究的重点。为了解决这个问题,本文提出了一种异构蜂窝网络中基于斯坦克尔伯格博弈的家庭基站与宏基站联合资源分配算法,算法首先基于图论的分簇算法对家庭基站和宏用户进行分簇和信道分配,以减少家庭基站之间的同层干扰和家庭基站层与宏蜂窝网络的跨层干扰;然后建立了联合家庭基站发射功率以及宏用户接入选择的斯坦克尔伯格博弈,推导出达到纳什均衡时的家庭基站发射功率的表达式,并据此为宏用户选择合适的接入策略。仿真结果表明,该算法能够有效地提高宏用户的信干噪比（SINR）,家庭用户的性能也得到改善。      

Distributed Resource Allocation for Femtocell Networks: Regret Learning with Proportional Self-belief

Femtocell networks promise improvement in network quality and performance for dense wireless networks, but will suffer from inter-cell interference if resource management is not properly employed. This paper presents distributed joint resource allocation (sub-channel and power) to address co- and cross-tier interference issues in two-tier heterogeneous femtocell networks. Due to uncoordinated nature of femtocell base stations (HeNB) deployment, the interactions among self-interested HeNBs are formulated using game-theoretical tools. Then, we designed individual utility function for every HeNB in order to enforce cooperative behaviour among HeNBs as well as to avoid cross-tier interference towards macrocell user equipments within HeNB coverage. Based on the designed utility function, we propose a fully distributed adaptive learning algorithm with a proportional self-belief concept that can lead to correlated equilibrium with fast and decisive convergence. Finally, performance analysis on the proposed algorithm done in simulated environment showed positive results indicating improvements in terms of co- and cross-tier interference mitigation as compared to generic regret-based learning scheme and utility functions.     

A multi‐cell adaptive resource allocation scheme based on potential game for ICIC in LTE‐A

Intercell interference coordination in Third Generation Partnership Project long‐term evolution‐advanced system has received much attention both from the academia and the standardization communities. Moreover, the network architecture of long‐term evolution‐advanced system is modified to take into account coordinated transmission. In this article, we study the dynamic resource allocation problem and potential game theory and propose a multicell adaptive distributed resource allocation algorithm based on potential game. The allocation process is divided into two steps; subchannel is allocated first, and then, transmitted power is optimized dynamically according to a novel pricing factor. Besides, existence and uniqueness of Nash equilibrium of the proposed game model are assured. As a result, intercell interference is well coordinated. Simulation results show that transmitted power is saved efficiently and system fairness is improved to a large extent, accompanied with good performance gain of total and cell‐edge throughputs. Copyright © 2013 John Wiley & Sons, Ltd.     

ESPS scheme for two‐tier interference suppression in a heterogeneous network with cooperative femtocells

The coexistence of a macrocell and a number of femtocells often leads to a two‐tier heterogeneous network, where the co‐tier interference (CotIN) and cross‐tier interference (CrotIN) both degrade users' quality of service. In order to suppress these interferences, we propose a precoding scheme in a heterogeneous network with cooperative femtocells, called CotIN elimination and CrotIN suppression with precoding criterion selection (ESPS) scheme. In this scheme, we first eliminate the CotINs of each user by applying the QR decomposition to channel matrix. Then the CrotINs of macrocell users and femtocell users are suppressed via the macrocell base station (MBS) and femtocell access points (FAPs) with precoding criterion selection, respectively. By using the ESPS scheme, spatial resources can be efficiently exploited. In addition, our ESPS scheme requires little information exchange between MBS and FAPs without iteration and thus significantly reduces the implementation complexity. Furthermore, the robustness is increased through introducing the information of channel uncertainty into the ESPS when channel estimation or quantization error exists. The performance analysis for the ESPS demonstrates that the ESPS is practical in the heterogeneous networks. Finally, simulation results show that the ESPS can decrease users' bit error rates and increase their transmission rates. Copyright © 2015 John Wiley & Sons, Ltd.     

Analytical evaluation of downlink interference mitigation in multi‐macrocell/femtocell networks with frequency & cell partitioning

In this paper, we propose an interference mitigation method to suppress the downlink interference in multi‐macrocell/femtocell networks, and analytically evaluate the interference mitigation and average rate performances. Specifically, the proposed interference mitigation method consists of three steps: frequency partitioning, cell partitioning, and sub‐band allocation. In the frequency partitioning step, the whole downlink frequency band is divided into nine non‐overlapping sub‐bands. In the cell partitioning step, each macrocell is divided into four macrocell regions and three femtocell regions for macrocells' and femtocells' communications, respectively. In the sub‐band allocation step, each macrocell or femtocell region is allocated a sub‐band to guarantee that any two neighboring macrocell/femtocell regions use different sub‐bands. Conducted simulation results show that the proposed method is effective in mitigating the downlink interference and improving the average downlink per‐channel rate in multi‐macrocell/femtocell networks. In summary, the major contribution of the proposed interference mitigation method is that the downlink interference can be mitigated without cooperation between macrocells and femtocells, while the full frequency utilization of the macrocell is achieved. Copyright © 2016 John Wiley & Sons, Ltd.     

Clustering‐based low‐complexity resource allocation in two‐tier femtocell networks with QoS provisioning

In this paper, we study the resource allocation problem of the uplink transmission with delay quality‐of‐service constraints in two‐tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra‐cluster subchannel allocation subproblem and inter‐cluster power control subproblem. Firstly, we develop a low‐complexity heuristic semi‐dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter‐cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter‐cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes. Copyright © 2015 John Wiley & Sons, Ltd.     

Distributed power control for multiuser cognitive radio networks with quality of service and interference temperature constraints

One of the most challenging problems in dynamic resource allocation for cognitive radio networks is to adjust transmission power of secondary users (SUs) while quality of service needs of both SUs and primary users (PUs) are guaranteed. Most power control algorithms only consider interference temperature constraint in single user scenario while ignoring the interference from PUs to SUs and minimum signal to interference plus noise ratio (SINR) requirement of SUs. In this paper, a distributed power control algorithm without user cooperation is proposed for multiuser underlay CNRs. Specifically, we focus on maximizing total throughput of SUs subject to both maximum allowable transmission power constraint and SINR constraint, as well as interference temperature constraint. To reduce the burden of information exchange and computational complexity, an average interference constraint is proposed. Parameter range and convergence analysis are given for feasible solutions. The resource allocation is transformed into a convex optimization problem, which is solved by using Lagrange dual method. In computer simulations, the effectiveness of our proposed scheme is shown by comparing with distributed constrained power control algorithm and Nash bargaining power control game algorithm. Copyright © 2014 John Wiley & Sons, Ltd.     

Distributed SNR-Based Power Allocation in Wireless Parallel Amplify-and-Forward Relay Transmissions Using Cournot Game

In wireless communications, power allocation plays a paramount role in sustainable network lifetime prolongation with quality-of-service and network interference reduction. This paper investigates a distributed power allocation problem in wireless parallel amplify-and-forward (AF) relay transmissions. Particularly, the objective is set to minimize the total transmit power while guaranteeing the signal-to-noise ratio (SNR) requirement at the destination node. The distributed SNR-based power allocation problem is formulated and modeled as a Cournot game. Moreover, a distributed SNR-based power allocation algorithm is proposed to solve the Cournot game. The proposed distributed SNR-based power allocation algorithm is proved to converge to a unique equilibrium. To evaluate the distributed method, a centralized optimal SNR-based power allocation algorithm is also proposed. Numerical results show that the proposed distributed SNR-based power allocation algorithm can achieve comparable performance to the centralized optimal SNR-based power allocation algorithm.     

Stackelberg game based interference management for two-tier femtocell networks

Femtocell is viewed as a promising option for mobile operators to improve coverage and provide high-data-rate services in a cost-effective manner. This paper considers the uplink interference management problem in a spectrum-sharing femtocell network. Assuming that the macrocell base station (MBS) is rewarded for sharing the spectrum with femtocells by setting a reasonable interference cap (IC) for femtocell users’ (FUEs’) transmissions. Within IC, the FUEs allocate their transmission powers competitively while not introducing much interference to both the macrocell users (MUEs) and other FUEs. A Stackelberg game is formulated to jointly maximize the utility of MBS and the individual utility of FUEs. Specifically, the maximum tolerable interference at the MBS is used as the resource that the leader (MBS) and the followers (FUEs) compete for. Then, the backward induction method is applied to achieve the Stackelberg equilibrium and a distributed power update rule is developed for FUEs. In addition, the implementation protocol is presented, some issues related to the implementations and some future extensions regarding the MUEs’ uplink protection are discussed. Lastly, numerical results demonstrate the performance of our proposed power allocation in detail, and show the effects of varying the number of FBSs and changing other system parameters on the system’s performance.     

Energy efficiency optimization algorithm for heterogeneous NOMA network based on imperfect CSI

In order to improve the suppression capability of parametric perturbation and energy efficiency (EE) of heterogeneous networks (HetNets),a robust resource allocation algorithm was proposed to maximize system EE for reducing cross-tier interference power in non-orthogonal multiple access (NOMA) based HetNets.Firstly,the resource optimization problem was formulated as a mixed integer and nonlinear programming one under the constraints of the interference power of macrocell users,maximum transmit power of small cell base station (BS),resource block assignment and the quality of service (QoS) requirement of each small cell user.Then,based on ellipsoid bounded channel uncertainty models,the original problem was converted into the equivalent convex optimization problem by using the convex relaxation method,Dinkelbach method and the successive convex approximation (SCA) method.The analytical solutions were obtained by using the Lagrangian dual approach.Simulation results verifiy that the proposed algorithm had better EE and robustness by comparing it with the existing algorithm under perfect channel state information.