Macrocell User Equipments Research Articles

Non-orthogonal transmission for user and control plane split architecture in 5G systems and beyond: Performance analysis and design insights

In next generation networks, mobility management will be a critical issue due to dense base station (BS) deployment, for which user and control plane split architecture provides a promising solution. Jointly designing such architecture with nonorthogonal transmission brings in more flexibility to further improve system efficiency. This paper proposes a non-orthogonal transmission design for user and control plane split architecture. In this design, user equipments (UEs) will select the BS providing the strongest received signal to associate its data channel, but constantly connect its control channel to the nearest macro-cell BS (MBS). Upon non-orthogonal transmission, an MBS can multiplex data traffics and control signals on the same resource. Stochastic geometry based analysis is carried out to investigate outage probability, which extends its regular definition by jointly considering data and control channels, and then mobility-aware outage rate. Numerical results show that: 1) The proposed split architecture alleviates the increase in handover rate for ultra dense networking, compared with conventional architecture. 2) Non-orthogonal transmission outperforms traditional orthogonal transmission in the split architecture, because it is capable of accommodating more control channels. 3) By carefully adjusting power levels, minimum outage probabilities can be reached for macro-cell UEs in the proposed design.

MM-Wave HetNet in 5G and beyond Cellular Networks Reinforcement Learning Method to improve QoS and Exploiting Path Loss Model

This paper presents High density heterogeneous networks (HetNet) which are the most promising technology for the fifth generation (5G) cellular network. Since 5G will be available for a long time, previous generation networking systems will need customization and updates. We examine the merits and drawbacks of legacy and Q-Learning (QL)-based adaptive resource allocation systems. Furthermore, various comparisons between methods and schemes are made for the purpose of evaluating the solutions for future generation. Microwave macro cells are used to enable extra high capacity such as Long-Term Evolution (LTE), eNodeB (eNB), and Multimedia Communications Wireless technology (MC), in which they are most likely to be deployed. This paper also presents four scenarios for 5G mm-Wave implementation, including proposed system architectures. The WL algorithm allocates optimal power to the small cell base station (SBS) to satisfy the minimum necessary capacity of macro cell user equipment (MUEs) and small cell user equipment (SCUEs) in order to provide quality of service (QoS) (SUEs). The challenges with dense HetNet and the massive backhaul traffic they generate are discussed in this study. Finally, a core HetNet design based on clusters is aimed at reducing backhaul traffic. According to our findings, MM-wave HetNet and MEC can be useful in a wide range of applications, including ultra-high data rate and low latency communications in 5G and beyond. We also used the channel model simulator to examine the directional power delay profile with received signal power, path loss, and path loss exponent (PLE) for both LOS and NLOS using uniform linear array (ULA) 2X2 and 64x16 antenna configurations at 38 GHz and 73 GHz mmWave bands for both LOS and NLOS (NYUSIM). The simulation results show the performance of several path loss models in the mmWave and sub-6 GHz bands. The path loss in the close-in (CI) model at mmWave bands is higher than that of open space and two ray path loss models because it considers all shadowing and reflection effects between transmitter and receiver. We also compared the suggested method to existing models like Amiri, Su, Alsobhi, Iqbal, and greedy (non adaptive), and found that it not only enhanced MUE and SUE minimum capacities and reduced BT complexity, but it also established a new minimum QoS threshold. We also talked about 6G researches in the future. When compared to utilizing the dual slope route loss model alone in a hybrid heterogeneous network, our simulation findings show that decoupling is more visible when employing the dual slope path loss model, which enhances system performance in terms of coverage and data rate.

Multiplexing Capacity of Hybrid PD-SCMA Heterogeneous Networks

Hybrid multiple access schemes are considered potential technologies towards achieving optimal spectrum sharing for future heterogeneous networks. Multiple users are multiplexed on a single resource unit in the code domain for sparse code multiple access (SCMA) or power domain for power domain non-orthogonal multiple access (PD-NOMA) and in both domains for the hybrid power domain sparse code non-orthogonal multiple access (PD-SCMA). This allows for effective spectrum usage but comes at a cost of increased detection complexity resulting in loss of performance in terms of outages. It is therefore imperative to determine the user multiplexing capacity for effective performance. This work investigates codebook capacity bounds in small cells, pairing and power capacity bounds for the number of small cell user equipment’s (SUEs) and macro cell user equipment’s (MUEs) that can be multiplexed on a codebook for the developed PD-SCMA technology. Closed-form solutions for codebook, pairing and power multiplexing capacity bounds are derived. The performance of the system results into low outage when the system’s point of operation is within the multiplexing bounds. To alleviate the resource allocation (RA) challenges of such a system at the transmitter, dual parameter ranking (DPR) and alternate search method (ASM) based RA schemes are proposed. The results show significant capacity gain with DPR-RA in comparison with conventional schemes.

Relay-Based Clustering Method for Interference Management in Heterogeneous Wireless Cellular Network

Femtocell is one of solutions to improve quality of services and network capacity for users in indoor areas. Radio resources used by femtocells are shared from macrocell network, thus it saves the use of frequency spectrum. However, one of problems in deploying femtocells within coverage area of macrocells is interference due to radio resources sharing between femtocells and macrocells. It creates interferences called as cross-tier (macrocell-femtocell/femtocell-macrocell) and co-tier (macrocell-macrocell/femtocell-femtocell) interferences. This paper proposes a relay-based clustering method to mitigate interference in femtocells located in the whole edge area of macrocell and the cell edge area of sectorized macrocells. Relay nodes are deployed statically (fixed location) in the neighboring macrocell area. Relay node will recruit their members based on the shortest distance. Certain relay node’s members do not need to transmit large amounts of power to enhanced Node B (eNB), such that interference from Macrocell User Equipment (MUE) to Home enhanced Node B (HeNB) can be minimized. Simulation experiments has been carried out and optimistic results for the sectorized macrocells scenario show that Signal-to-Interference-plus-Noise-Ratio (SINR) of femtocells for the conventional system that does not reach the targeted SINR of 20 dB is 87%. Meanwhile, after applying the relay-based clustering method, SINR value of femtocells below or equal to 20 dB reaches 72%. Optimistic results for throughput and Bit Error Rate (BER) show improvement of 15% and 14%, respectively. It has been shown that the relay-based clustering method can provide better performance compared to the conventional system even for femtocells densely deployed.

Bargaining solutions in heterogeneous networks: A reinforcement learning‐based approach

To enhance the performance and the coverage area of the next-generation heterogeneous wireless networks (HetNets), smaller cells such as femtocells are deployed. A reasonable resource allocation strategy is crucial for the operation of such systems. In this work, the Nash bargaining solution (NBS), Kalai–Smorodinsky bargaining solution (KSBS), and a proposed bargaining solution, which is the combination of NBS and KSBS, are studied to ensure the efficiency and fairness in the transmission rate allocation among femtocells. The mentioned bargaining solutions are optimised subject to the rate constraints due to the Han–Kobayashi (HK) rate splitting scheme, and a maximum tolerable interference caused by femtocell base stations (FBSs) at the macrocell user equipment. Two methods are used to address the bargaining solutions' optimisations. First, the conventional optimisation-based method is used for the situations where the channel gains are known, then a reinforcement learning-based algorithm for a real environment is proposed without being aware of the channel gains. To accelerate the speed of the learning process and to initialise the values of quality functions, the hotbooting technique is used. The bargaining solutions are compared by fairness and efficiency criteria in both methods. Numerical simulations show that the proposed reinforcement learning-based algorithm achieves the same performance derived from the conventional optimisation method. First, this paper studies the two well-known Nash and Kalai–Smorodinsky bargaining solutions as the good tools to establish fairness in rate allocation problem among femtocells in a HetNet. Then a new bargaining solution is proposed as the combination of the two bargaining solutions. The fairness and the efficiency of the allocated rates to femtocells as the output of optimisation problems of bargaining solutions are compared via Jain index criterion (as the fairness metric) and inverse price of anarchy criterion (as the efficiency metric). Moreover, the femtocell base stations are allowed to use Han–Kobayashi signalling scheme to send their signals in private and common messages which results in the best-known achievable rate region. Two methods are used to solve the optimisation problems: the conventional optimisation method and the reinforcement learning-based method (to formulate a real-world model with the unknown channel gains). It is shown that the proposed bargaining solution (in both methods) results in fairer rates than Nash and Kalai–Smorodinsky bargaining solutions while all of them are efficient.

Interference Mitigation in HetNets to Improve the QoS Using Q-Learning

Small cells (SCs) based ultra-dense heterogeneous networks (HetNets) are one of the promising solutions for increased coverage and capacity in 5G cellular networks. However, in multi-tiered architecture, co-tier and cross-tier interferences are both performance-limiting factors. Efficient resource allocation techniques can handle interferences effectively, however, their complexity linearly increases with the density of the HetNets resulting from dynamic and unplanned deployment of SCs. Therefore, HetNets can be implemented only through an algorithm that is self-organizing and adaptive to the dynamic conditions. In this research article, a Q-Learning (QL) based adaptive resource allocation scheme is proposed and evaluated for SC-based ultra-dense HetNets. This QL scheme allocates optimal power to the small cell base station (SBS) to meet the minimum required capacity of macrocell user equipment (MUEs) and the small cell user equipment (SUEs) to provide quality of service (QoS). The proposed QL scheme not only maintains the minimum required capacities of the MUEs and SUEs but has also shown a significant improvement in the capacities of MUEs and SUEs in high interference scenarios as compared to the prior works. In the high co-tier and cross-tier interference scenario, where the state of the art schemes fail to maintain the minimum required capacity of the MUE, the proposed scheme provides a minimum MUE capacity of 2 b/s/Hz, which is twice the minimum required QoS threshold. In a similar way, the proposed solution guarantees QoS up to 16 SCs which are 37.5% more SC than the previously reported works in high interference scenario while maintaining a minimum SUE capacity of 1.5 b/s/Hz, which is 33% higher than the minimum required QoS threshold. By simultaneously mitigating co-tier and cross-tier interferences in ultra-dense HetNets, the proposed solution not only improved the minimum capacities of MUEs and SUEs but also sets a new benchmark for minimum QoS threshold.

Cluster-based Access Control Mechanism for Cellular D2D Communication Networks with Dense Device Deployment

In cellular device-to-device (D2D) communication networks, devices can communicate directly with each other without passing through base stations. Access control is an important function of radio resource management which aims to reduce frequency collision and mitigate interference between user’s connections. In this paper, we propose a cluster-based access control (CBAC) mechanism for heterogeneous cellular D2D communication networks with dense device deployment where both the macro base station and smallcell base stations (SBSs) coexist. In the proposed CBAC mechanism, relied on monitoring interference from its neighboring SBSs, each SBS firstly selects their operating bandwidth parts. Then, it jointly al-locates channels and assigns transmission power to smallcell user equipments (SUEs) for their uplink transmissions and users using D2D communications to mitigate their interference to uplink transmissions of macrocell user equipments (MUEs). Through computer simulations, numerical results show that the proposed CBAC mechanism can provide higher network throughput as well as user throughput than those of the network-assisted device-decided scheme proposed in the literature. Simulation results also show that SINR of uplink transmissions of MUEs and D2D communications managed by the MBS can be significantly improved.

Precoding Based Cross-Tier Interference Mitigation in Centralized-RAN

This letter considers a two-tier downlink interference problem as a case of study, where macrocell user equipment (UE) shares the same frequency band with femtocell UE and suffers from severe cross-tier interference. Power control is one of the spectrally-efficient techniques used to mitigate the interference. However, it harms femtocell users since the femto base station reduces the transmitted power. In this letter, a novel scheme is proposed to jointly suppress the interference on the macrocell users, and preserve the high data rates required by femtocell users under centralized radio access network. The analytical results well agreed with the conducted simulations, and showed the superiority of the proposed scheme in achieving higher throughput compared to existing schemes.

Joint subchannel assignment and power control in OFDMA in‐band full‐duplex heterogeneous networks

AbstractAmong the emerging technologies for the fifth‐generation (5G) cellular networks, in‐band full‐duplex (FD) wireless communication and heterogeneous networks (HetNets) are two promising technologies, which can significantly improve the network capacity. Due to self‐interference (SI) and multiple sources of intercell interference, base station (BS)‐BS interference and user equipment (UE)‐UE interference in FD HetNets, interference management is a significant and challenging issue in such a network. To this end, in this article, we study the joint subchannel assignment and power control problem in the OFDMA FD HetNet. The joint subchannel assignment and power control problem in this network is formulated as an optimization problem to maximize the uplink and downlink sum throughput of the femtocell user equipments (FUEs) taking into account the maximum interference constraint imposed on the macrocell user equipments (MUEs) and the minimum throughput constraint of FUEs. Since the formulated problem is a nonconvex and intractable mixed integer nonlinear programming (MINLP) problem, we invoke variable change and linear approximation to reformulate and convert the problem into a tractable mixed‐integer linear programming (MILP) problem. Numerical results show that the optimal solution of the new MILP problem is very close to the optimal objective value of the original MINLP problem. The results also demonstrate that in an OFDMA FD HetNet, when all the UEs and the BSs are FD, approximately 50% improvement in the network throughputcan be achieved compared with a half‐duplex HetNet.

Heterogeneous Networks in 5g using Joint Path Selection and Rate Allocation Framework

One of the major challenges in evolving wireless cellular networks whose return network is constrained by capability and heterogeneity (wired, wireless, and hybrid) is the design of distributed management mechanism. This study proposes a new method of managing wireless network interference with the ability to detect return network. The proposed approach helps Macro-cell User Equipment (MUE) to maximize its output using adjacent small cell base stations to maximize its uplink. Considering the radio access network and backhaul (possibly heterogeneous), this issue is represented as a non-cooperative game between MUE that attempts to maximize its compensation for delay levels. A new distributed learning algorithm is proposed to solve this problem, which uses the algorithm to autonomously choose the best uplink transmission strategy, provided a limited amount of available knowledge. The algorithm's convergence is demonstrated, and its output is studied. The simulation results show that, in comparison to the existing reference algorithm, The proposed approach has substantial efficiency benefits for various forms of backhaul in terms of average output and delay in MUE.

Biological Resource Allocation Algorithms for Heterogeneous Uplink PD-SCMA NOMA Networks

Due to their ability to multiplex users on a resource element (RE), Non-orthogonal multiple access (NOMA) techniques have gained popularity in 5G network implementation. The features of 5G heterogeneous networks have necessitated the development of hybrid NOMA schemes combining the merits of the individual NOMA schemes for optimal performance. The hybrid technologies on 5G networks make complex air interfaces resulting in new resource allocation (RA) and user pairing (UP) challenges aimed at limiting the multiplexed users interference. Furthermore, common analytical techniques for evaluating the performance of the schemes lead to unrealistic network performance bounds necessitating alternative schemes. This work explores the feasibility of a hybrid power domain sparse code non-orthogonal multiple access (PD-SCMA). The scheme integrates both power and code domain multiple access on an uplink network of small cell user equipments (SUEs) and macro cell user equipments (MUEs). Alternative biological RA/UP schemes; the ant colony optimization (ACO), particle swarm optimization (PSO) and a hybrid adaptive particle swarm optimization (APASO) algorithms, are proposed. The performance results indicate the developed APASO outperforming both the PSO and ACO in sum rate and energy efficiency optimization on application to the PD-SCMA based heterogeneous network.

Interference management for D2D‐enabled HetNets with imperfect channel estimation

Device-to-device (D2D) and heterogeneous networks (HetNets) are two promising technologies to be introduced in the upcoming 5G network, for improving spectral efficiency and decreasing latency. However, sharing the same spectrum resources among different tiers of HetNet raised the interference challenge. In this paper, cross-tier interference management for underlay D2D users is studied in a heterogeneous macro-small cell network assuming imperfect channel state information (CSI). The network consists of one macro-cell with a centered macro-base Station (MBS) and several small-cell base stations (SCBS). Two types cellular users are considered; macro-cell cellular user equipment (MUE) associated with the MBS, and small-cell cellular user equipment (SUE) linked to SCBS. While two types of D2D users are considered; macrocell D2D (MD) located outside the range of the small cells and cross-tier D2D user equipment (CD), where each user of the D2D pair belongs to different network tier. Closed form expressions for the D2D optimal power that aim to maximize the coverage probability and the signal-to-interference-noise ratio (SINR) of both links are derived, while guaranteeing the quality of service (QoS) requirements for the cellular user. The effect of channel estimation error on the performance of both D2D and cellular users is evaluated.

A novel analytical model for interference estimation in CR‐enabled femtocells

SummaryCommercial, multideployed cognitive femtocell base stations (CFBSs) with cognitive capabilities are envisioned as a promising approach to meet the requirement of the higher data rate in today's wireless communications with nomadic users. However, random deployment of CFBSs results in interference between primary links, ie, the link between a macrocell base station (MBS) and macrocell user equipment (MUE), and secondary links, ie, the link between a femtocell base station (FBS) and femtocell user equipment (FUE). In this research paper, different analytical expressions for statistical measures such as cumulative distribution function of outage probability (Fout) and probability distribution function (Pout) have been proposed for the CFBS system. The fading channel for the secondary and primary links is taken as mixture gamma (MG) and Rayleigh distribution, respectively. It should be noticed that MG fading is one of the most generic fading channels and has not been included for analysis of the CFBS system to date. In addition, this paper presents average detection probability ( ) for cognitive radio (CR)–enabled femtocells or the CFBS system. The numerical analysis presents the effects of various parameters such as spatial density of CFBS nodes (λ), interference tolerance threshold (βth), and transmitting power of MBS (p) and fading parameters of the channel on Fout, Pout, and . Also, the numerical analysis shows perfect agreement with the theoretical background.

Power Control via Stackelberg Game for Small-Cell Networks

In this paper, power control in the uplink for two-tier small-cell networks is investigated. We formulate the power control problem as a Stackelberg game, where the macrocell user equipment (MUE) acts as the leader and the small-cell user equipment (SUE) acts as the follower. To reduce the cross-tier and cotier interferences and the power consumption of both the MUE and SUE, we propose optimizing not only the transmit rate but also the transmit power. The corresponding optimization problems are solved through a two-layer iteration. In the inner iteration, the SUE items (SUEs) compete with each other, and their optimal transmit powers are obtained through iterative computations. In the outer iteration, the optimal transmit power of the MUE is obtained in a closed form based on the transmit powers of the SUEs through proper mathematical manipulations. We prove the convergence of the proposed power control scheme, and we also theoretically show the existence and uniqueness of the Stackelberg equilibrium (SE) in the formulated Stackelberg game. The simulation results show that the proposed power control scheme provides considerable improvements, particularly for the MUE.

Joint Energy Efficient Subchannel and Power Optimization for a Downlink NOMA Heterogeneous Network

Non-orthogonal multiple access (NOMA) has been considered as a key technology in the fifth-generation mobile communication networks due to its superior spectrum efficiency. Since the heterogeneous network has been emerged to satisfy users' explosive data rate requirements and large connectivity of mobile Internet, implementing NOMA policy in heterogeneous networks (HetNets) has become an inevitable trend to enhance the 5G system throughput and spectrum efficiency. In this paper, we aim to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation. By considering the co-channel interference and cross-tier interference, the energy efficient resource allocation problem is formulated as a mixed integer nonconvex optimization problem. It is challenging to obtain the optimal solution; therefore, a suboptimal algorithm is proposed to alternatively optimize the macrocell and the small cells resource allocation. Specifically, convex relaxation and dual-decomposition techniques are exploited to optimize the subchannel allocation and power allocation. Moreover, optimal closed-form power allocation expressions are derived for small cell and macrocell user equipments by the Lagrangian approach. Simulations results show that the proposed algorithms can converge within ten iterations and can also attain higher system energy efficiency than the reference schemes.

Interference Management in LTE-Advanced Cooperative Relay Networks: Decentralized Transceiver Design With Channel Estimation

Wireless networks improve indoor communications by deploying femtocell networks into the macrocell coverage. This results in spectrum sharing with the consequences of cross-tier interference from the macrocell user equipment (MUEs) to the femtocell access points (FAPs). This work considers the uplink cross-tier interference management for the cell-edge MUEs (CUEs) in cooperative multi-user multiple input multiple output (MU-MIMO) systems. For better interference management, the CUEs are grouped into clusters and communicate to the macrocell base station (MBS) through a relay node (RN). The linear pre-coders and decoders algorithms for the FAPs, MUEs and CUEs are proposed for effective interference management to minimize the sum mean square error (MSE), subject to the total transmit power constraints. The designed pre-coders and decoders use the pilot-assisted channel estimation to improve the accuracy of the acquired channel state information (CSI). The least-square (LS) and minimum MSE (MMSE) channel estimators are considered. The performance of the system is investigated in terms of the bit error rate (BER) for the linear pre-coders and decoders algorithms with the pilot-assisted channel estimators.

TARCO: Two-Stage Auction for D2D Relay Aided Computation Resource Allocation in HetNet

In heterogeneous cellular network, task scheduling for computation offloading is one of the biggest challenges. Most works focus on alleviating heavy burden of macro base stations by moving the computation tasks on macro-cell user equipment (MUE) to remote cloud or small-cell base stations. But the selfishness of network users is seldom considered. Motivated by the cloud edge computing, this paper provides incentive for task transfer from macro cell users to small cell base stations. The proposed incentive scheme utilizes small cell user equipment to provide relay service. The problem of computation offloading is modelled as a two-stage auction, in which the remote MUEs with common social character can form a group and then buy the computation resource of small-cell base stations with the relay of small cell user equipment. A two-stage auction scheme named TARCO is contributed to maximize utilities for both sellers and buyers in the network. The truthful, individual rationality and budget balance of the TARCO are also proved in this paper. In addition, two algorithms are proposed to further refine TARCO on the social welfare of the network. Extensive simulation results demonstrate that, TARCO is better than random algorithm by about 104.90% in terms of average utility of MUEs, while the performance of TARCO is further improved up to 28.75% and 17.06% by the proposed two algorithms, respectively.

Tier‐aware joint subchannel and power allocation in uplink OFDMA heterogeneous networks

AbstractWe study the problem of tier‐aware subchannel and power allocation in the uplink of a two‐tier orthogonal frequency‐division multiple access heterogeneous network. We formulate the joint subchannel and power allocation problem in the macro‐tier as an optimization problem that is aware of the existence of the femto‐tier and aims to maximize the sum of tolerable interference caused by femto‐tier on its allocated subchannel(s) subject to the minimum data rate requirements of the macrocell user equipments (MUEs). The resource allocation problem for the macro‐tier is an NP‐hard mixed‐integer nonlinear programming (MINLP) problem. To address it, we reformulate and transform it to a tractable mixed‐integer linear programming (MILP) problem, which is optimally addressed with polynomial‐time complexity. We formulate the joint subchannel and power allocation problem in the femto‐tier as an optimization problem that is aware of the existence of the macro‐tier and aims to maximize the sum rate of the femtocell user equipments subject to the maximum tolerable interference caused to the MUEs. To address this MINLP problem, we transform it to a MILP problem through a linear approximation, which is solved optimally by IBM CPLEX solver. In addition, we develop a distributed and efficient algorithm that addresses this optimization problem suboptimally with a lower computational complexity. Numerical results show that our proposed algorithms outperform the existing algorithms in terms of network sum rate.

Performance Analysis of the Idle Mode Capability in a Dense Heterogeneous Cellular Network

In this paper, we study the impact of the base station (BS) idle mode capacity (IMC) on the network performance of multi-tier and dense heterogeneous cellular networks (HCNs) with both line-of-sight (LoS) and non-line-of-sight transmissions. Different from most existing works that investigated network scenarios with an infinite number of user equipments (UEs), we consider a more practical set-up with a finite number of UEs in our analysis. Moreover, in our model, the small BSs (SBSs) apply a positive power bias in the cell association procedure, so that macrocell UEs are actively encouraged to use the more lightly loaded SBSs. In addition, to address the severe interference that these cell range expanded UEs may suffer, the macro BSs (MBSs) apply enhanced inter-cell interference coordination, in the form of almost blank subframe (ABS) mechanism. For this model, we derive the coverage probability and the rate of a typical UE in the whole network or a certain tier. The impact of the IMC on the performance of the network is shown to be significant. In particular, it is important to note that there will be a surplus of BSs when the BS density exceeds the UE density, and thus a large number of BSs switch off. As a result, the overall coverage probability, as well as the area spectral efficiency, will continuously increase with the BS density, addressing the network outage that occurs when all BSs are active and the interference becomes LoS dominated. Finally, the optimal ABS factors are investigated in different BS density regions. One of major findings is that MBSs should give up all resources in favor of the SBSs when the small cell networks go ultra-dense. This reinforces the need for orthogonal deployments, shedding new light on the design and deployment of the future 5G dense HCNs.

Joint Subchannel and Power Allocation in Secure Transmission Design for Femtocell Networks

In this paper, a joint subchannel and power allocation problem is investigated for a downlink two-tier femtocell network system, where there exists an eavesdropper wiretapping a legitimate macrocell user equipment. We aim at improving security of a macrocell user using the existing beneficial interferences from other users to eavesdropper in dense femtocell networks. Cochannel interference in the same subchannel is considered to improve the secure transmission performance. The purpose of the problem under investigation is to propose a secure transmission scheme with joint subchannel assignment and power allocation. In the scheme, a subchannel assignment algorithm is proposed to search optimal subchannel assignment strategies. Furthermore, a noncooperative game framework with switch utility functions is formulated based on different service requirements of femtocell networks. Transmission securities of legitimate users are improved without consuming extra transmit power. Then, iterative algorithms for the problem are given. Finally, numerical results are presented to illustrate the validity of the proposed secure transmission scheme.