Joint Power and Bandwidth Allocation Algorithm with QoS Support in Heterogeneous Wireless Networks

Equal allocation of bandwidth and/or power may not be efficient for wireless multi-user networks with limited bandwidth and power resources. Optimal joint bandwidth and power allocation strategies for wireless multi-user networks with and without relaying are proposed in this paper for (1) the maximization of the sum capacity of all users; (2) the maximization of the worst user capacity; and (3) the minimization of the total power consumption of all users. It is shown that the proposed allocation problems are convex and, therefore, can be solved efficiently. Moreover, joint bandwidth and power allocation for admission control is considered. A suboptimal greedy search algorithm is developed to solve the admission control problem efficiently. Instructive analysis of the greedy search shows that it can achieve good performance, and the condition under which the greedy search is optimal is derived. The formal and in-depth analysis of the greedy search algorithm presented in this paper can serve as a benchmark for analyzing similar algorithms in other applications. The performance improvements offered by the proposed optimal joint bandwidth and power allocation are demonstrated by simulations. The advantages of the suboptimal greedy search algorithm for admission control are also shown in numerical results.

A QoE-based Joint Bandwidth and Power Allocation Method for Multiple RATs in HetNets

The explosive demands for mobile broadband service bring a major challenge to 5G wireless networks. Device-to-device communication, adopting side links for user-direct communication, is regarded as a main technical source for offloading large volume of mobile traffic from cellular base station. This article investigates the joint power and subcarrier allocation scheme for device-to-device communication in 5G time division duplex systems. In time division duplex system, instead of utilizing an exclusive portion of the precious cellular spectrum, device-to-device pairs reuse the subcarriers occupied by cellular users, thus producing harmful interference to cellular users in both uplink and downlink communication, and strongly limiting the spectrum efficiency of the system. To this end, we focus on the maximization of device-to-device throughput while guaranteeing both uplink and downlink channel quality of service of cellular users as well as device-to-device pairs. The problem is formulated as a mixed integer non-linear programming (MINLP) problem. To make it tractable, we separate the original MINLP problem into two sub problems: power allocation and sub-carrier reusing. The former is to develop optimal power allocation for each device-to-device pair and each cellular user, with the constraints of maximum power and quality of service. It is solved by geometric programming technique in convex optimization method. The latter is derived as a one-to-many matching problem for scheduling multiple subcarriers occupied by cellulars to device-to-device pairs. It is solved by Hungarian method. Simulation results show that the proposed scheme significantly improves system capacity of the device-to-device underlay network, with quality of service of both device-to-device users and cellular users guaranteed.

SummaryWe investigate the problem of joint downlink wireless backhaul bandwidth (WBB) and power allocation in heterogeneous cellular networks (HCNs). A WBB partitioning scheme is considered, which allocates the whole bandwidth between the macrocell and small cells for data transmission and backhauling. We formulate an optimization problem to maximize the weighted sum logarithmic utility function by jointly optimizing WBB portion and fronthaul power allocation of each base station with consideration of the backhaul capacity limitation on each small cell. In order to solve this joint optimization problem, we propose a hierarchical two‐level approach and decompose the original problem into two independent subproblems: the WBB allocation at the macrocell base station (MBS) and the power allocation at both the MBS and small cell base stations (SBSs). Accordingly, the optimal WBB portion and power allocation solutions are obtained, respectively. Furthermore, we develop a distributed algorithm to implement the joint WBB and power allocation. Numerical results verify the effectiveness of the proposed approach and analyze the impact of the weighted coefficient and backhaul capacity limitation on the network performance. In addition, significant performance gains can be achieved by the proposed approach over the benchmark.

With the drastic increase of space information network (SIN) traffic and the diversity of network traffic types, the optimal allocation of the scarce network resources is of great significance for optimizing the SIN system capability. In this paper, we propose a multi-resource management method for multi-tier SIN using the cooperative Nash bargaining solution. Since the original problem is a non-convex problem, we firstly make logarithmic transition, and then find a tightest lower bound function to convert the initial problem into a convex one. In order to carry out the optimal bandwidth and power allocation in SIN, we construct a joint bandwidth and power allocation (JBPA) algorithm. Simulation results show the performance improvement of the JBPA scheme and the convergence of JBPA algorithm.

As an effective approach to alleviate the spectrum scarcity problem, cognitive radio (CR) has recently attracted an increasing amount of attention. In this paper, an optimization algorithm that joints bandwidth and power allocation of hybrid spectrum sharing is proposed in CR. According to the location variation of cognitive user (CU) that adopt the random waypoint based mobility models, the state of CU can switch between Underlay spectrum sharing model and Overlay spectrum one. Simultaneously, this algorithm can maximize the channel capacity through jointly optimizing power and bandwidth of CU when the Primary User's (PU's) interference temperature and the CU's transmission can be satisfied. Simulation results show that the proposed algorithm can more effectively improve the channel capacity than the single Underlay system and traditional solutions that the bandwidth is evenly allocated.

A novel multibeam satellite system design is proposed in this paper based on jointly optimizing power and carrier allocation in order to best match the asymmetric traffic requests. This design introduces higher and asymmetric interference levels throughout the coverage. However, both power and bandwidth will be used more efficiently. Even though the problem of power and bandwidth allocation has been addressed in terrestrial wireless communications, it is new in satellite systems and since architecture and channel are different, available results and algorithms are not applicable to satellite payload systems. In this paper we formulate the resource allocation problem as max-min SINR balancing based on the recently introduced axiomatic-based interference model, but in addition, we also optimize the carrier allocation when performing the SINR balancing problem. An analytical solution for the optimal carrier allocation is proposed and we iteratively find the optimal power allocation for each beam. The Shannon (upper bound) and current state-of-the art PHY layer technology: DVB-S2 are proposed to be implemented in order to obtain the gap between them. Simulation results show significant improvements in terms of power gain, spectral efficiency and traffic matching ratio comparing with conventional system, which is designed based on uniform bandwidth and power allocation.

Cognitive radio and heterogeneous wireless networks are important candidate techniques for the fifth generation (5G) communication systems. On the other hand, propagation properties of radio channels in a physical layer are exploited to design efficient secure transmission schemes for 5G wireless networks. In this work, a security-aware joint power and subchannel allocation problem based on the inter-network cooperation is investigated at cognitive heterogeneous networks via imperfect spectral sensing. The security-aware joint power and subchannel allocation is subject to constraints in available subchannels, proportional fairness secrecy transmission rates among secondary mobile terminals (MTs), total interference power threshold, and total power for each secondary MT. In order to determine the impact of imperfect spectral sensing to resource allocation, we first represent the interference power at primary base station in terms of the misdetection probability and false alarm probability. Then, the security-aware power and subchannel allocation problem with inter-network cooperation is formulated as a biconvex optimization problem, and an optimal security-aware power and subchannel allocation algorithm is proposed utilizing the dual decomposition method. Compared to the heuristic power and subchannel allocation algorithms, numerical simulation results show that the proposed algorithms improve the total secrecy throughput and guarantee the proportional fairness among different secondary MTs.

Heterogeneous networks (HetNets) composed of macrocells and small cells are expected to improve the transmission performance of users significantly. Designing efficient resource allocation schemes, specifically, bandwidth allocation and power allocation schemes for HetNets is of particular importance for it may affect user quality of service (QoS) and network performance severely. In this paper, we consider the resource allocation problem of a HetNet composed of a macrocell and a number of femtocells and propose a resource characteristic and user QoS oriented bandwidth and power allocation algorithm for the femto base stations (FBSs) which share spectrum with the macro base station. By taking into account the service requirements of the femto user equipments (FUEs) and the bandwidth resource characteristics of the network, various bandwidth resource allocation schemes are proposed. Particularly, in the case of slightly insufficient bandwidth resource, we propose a bankruptcy game based bandwidth resource allocation algorithm for the FBSs, and solve the bandwidth allocation problem by means of Shapley value method. To stress the tradeoff between data rate and power consumption, we examine the energy efficiency of the FBSs and formulate the power allocation problem as a multi-objective optimization problem with the objectives of maximizing the energy efficiency of all the FBSs. The optimal power allocation strategy can be obtained by solving the optimization problem via ideal point method and generic algorithm. Simulation results demonstrate the efficiency of the proposed algorithm.

In heterogeneous cellular networks (HCNs), the growing demand of small cell data traffic puts great pressure on the capacity limited backhaul links. Resource allocation is an efficient approach to mitigate the severe interference and improve the network performance in HCNs. However, differentiated backhaul capacity constraints introduce the inherent nonconvexity to the resource optimization problem, which hinders the development of the optimal solutions. In this article, we investigate the joint resource block (RB) and power allocation problem under two different backhaul capacity limitations. First, we consider the small cell backhaul limitation scenario where the backhaul capacity constraint is imposed on each small cell. Then, we extend the resource optimization to the macrocell base station backhaul limitation scenario which considers the overall backhaul capacity constraint on the whole small cell network. Besides, the quality of service (QoS) requirements of users and the cross‐tier interference mitigation are also considered. This resource allocation problem is formulated as a nonconvex mixed‐integer nonlinear programming (MINLP) problem. By variable substitution and constraints relaxation, we convert the original optimization problem into a convex one and obtain the optimal solutions. Accordingly, joint RB and power allocation algorithms are proposed. Numerical results verify the effectiveness of the proposed algorithms and evaluate the impact of different types of backhaul capacity limitations on system performance.

This paper presents a genetic approach for joint relay selection, bandwidth allocation and power distribution in multi-user Decode-and-Forward (DF) cooperative networks. To accommodate this joint consideration, each chromosome in the proposed genetic algorithm (GA) is divided into an integer string for relay selection and two real number strings for bandwidth allocation and power distribution. In addition, new crossover and mutation operations are employed for this new type of chromosomes. Conducted simulations show that the proposed GA-based approach can attain close performance as the upper bound and outperforms some representative previous works.

We consider two-way amplify-and-forward relaying in a multichannel system with two end nodes and a single relay, using a two-slot multi-access broadcast (MABC) relaying strategy. We investigate the problem of joint subchannel pairing and power allocation to maximize the achievable sum-rate in the network, under an individual power budgets at each node. To solve this challenging joint optimization problem, an iterative approach is proposed to decompose the problem into pairing optimization and joint power allocation optimization, and solve them iteratively. For the joint power allocation at the relay and the two end nodes, we propose another iterative optimization procedure to optimize the power at the two end nodes and at the relay iteratively. By using different forms of optimization parameters, the sum-rate maximization problem turns out to be convex and the optimal solutions can be obtained for each subproblem. The simulation performance demonstrates the gain of joint optimization approach over other pairing-only or power-allocation-only optimization approaches.

This paper studies the case of an overlay cognitive radio network where the primary user leases spectral resources to the secondary user in exchange for cooperation, considering that both type of users have specific quality of service requirements. We investigate the problem of joint power and time allocation for the secondary access during the cooperative phase, with a view to optimizing the effective capacity of the primary user given an average energy constraint for the secondary user. Afterwards, the optimal power allocation of the secondary user for its own transmission phase is investigated in order to maximize the effective capacity of the secondary link. The proposed joint power and time allocation mechanism is compared with an optimal time/constant power allocation scheme and a less sophisticated baseline allocation scheme, i.e. power allocation under constant time and its superiority is proven for various network parameters. The reference model of one primary---one secondary user is extended to a general multi user cognitive radio network through the proposed pairing mechanism based on matching theory. Particularly, considering the remarks of the reference scenario, we propose two different matching schemes (with/without consideration of primary users' quality of service requirements) and we confirm their superiority compared to other matching mechanisms.

This paper presents a dynamic bandwidth allocation scheme for multiple services in heterogeneous networks. A utility function is introduced first, whose parameters are determined by the modified multi-state Analytic Hierarchy Process (AHP) which adapts to different load levels according to dynamic thresholds. Based on this, a bandwidth allocation algorithm is proposed for Constant Bit Rate (CBR) and Variable Bit Rate (VBR) services depending on not only utility fairness among different networks, but also the fairness between new arrival and ongoing services. Simulation results show that the proposed algorithm is effective in guaranteeing both the fairness of the edge users and the network system performance, i.e. keeping low block probability in the wireless network system.

In this paper, a joint subcarrier and power allocation algorithm is proposed to improve the physical layer security in cooperative orthogonal frequency division multiple access (OFDMA) networks, where several source-destination pairs and one untrusted relay are involved. The relay is friendly and intends to help these pairs to enhance their communications. However, it may be overheard by a malicious eavesdropper at the same time. To optimize the joint subcarrier and power allocation with low complexity, we divide the optimization problem into two simpler subproblems. Firstly, the subcarriers are assigned to the source-destination pairs by employing the dual approach under the assumption that the relay power is equally allocated to all the subcarriers. Then, the relay power is allocated to the subcarriers based on the alternative ascending clock auction mechanism. In addition, we prove that the two subproblems can converge after a finite number of iterations. We also find that the proposed auction is cheat-proof and, thus, can avoid the cheating behaviors in the auction process. Numerical results demonstrate that our proposed algorithm can effectively improve the system sum secrecy rate, and the convergence performance is also desirable.