In this paper, a macro cell switching scheme for distributed antennas is proposed. In conventional distributed antenna transmission (DAT), the macro cell to which each antenna belongs is fixed. Though a cell-free system has been investigated because of its higher system throughput, the implementation cost of front-hauls can be excessive. To increase the flexibility of resource allocation in the DAT with moderate front-haul complexity, we propose the macro cell switching of distributed antennas (DAs). In the proposed scheme, DAs switch their attribution macro cells depending on the amount of pre-assigned connections. Numerical results obtained through computer simulation show that the proposed scheme realizes a better system throughput than the conventional system, especially when the number of user equipments (UEs) is smaller and the distance between DAs are larger.

In small cell deployments, the combined usage of user association and inter-cell interference coordination (ICIC) is inevitable. This paper investigates the joint optimization of user association and ICIC in the downlink. We first formulate the joint optimization problem as a utility maximization problem. We then employ the logarithmic utility function known as the proportional fair criteria. The optimum user association and the ICIC are derived by solving a convex optimization problem based on the average spectral efficiencies of all users. We propose an iterative algorithm to obtain the optimum solution to this problem. We evaluate the performance of the proposed algorithm for the small cell deployments and shows that the proposed algorithm works well. We also compare the performance of the proposed algorithm based on utility maximization user association with the CRE, and show the superiority of the utility maximization. Furthermore, we show that intra-tier ICIC and inter-tier ICIC can effectively improve the throughput performance according to the conditions. It is also shown that the combined usage of inter-tier ICIC and intra-tier ICIC enhances the throughput performance compared to schemes employing either the inter- or intra-tier ICIC scheme.

In this letter, we consider the power allocation scheme with rate proportional fairness to maximize energy efficiency in the downlink the non-orthogonal multiple access (NOMA) systems. The optimization problem of energy efficiency is a non-convex optimization problem, and the fractional programming is used to transform the original problem into a series of optimization sub-problems. A two-layer iterative algorithm is proposed to solve these sub-problems, in which power allocation with the fixed energy efficiency is achieved in the inner layer, and the optimal energy efficiency of the system is obtained by the bisection method in the outer layer. Simulation results show the effectiveness of the proposed algorithm.

In cellular network environments, where users are not evenly distributed across cells, overloaded base stations handling many users have difficulties in providing effective and fair services with their limited resources. Additionally, users at the cell edge may suffer from the potential problems resulting from low signal-to-interference ratio owing to the incessant interference from adjacent cells. In this paper, we propose a relay-assisted load balancing scheme to resolve these traffic imbalance. The proposed scheme can improve the performance of the overall network by utilizing relay stations to divert heavy traffic to other cells, and by adopting a partial frequency-reuse scheme to mitigate inter-cell interference. Each user and relay station calculates its own utility influence in the neighboring candidates for reassociation and decides whether to stay or move to another cell presenting the maximum total network utility increment. Simulation results show that the proposed scheme improves the overall network fairness to users by improving the performance of cell boundary users without degrading the total network throughput. We achieve a system performance gain of 16 ∼ 35% when compared with conventional schemes, while ensuring fairness among users.

In this letter, we investigate the price-based power allocation with rate proportional fairness constraint in downlink non-orthogonal multiple access (NOMA) systems. The Stackelberg game is utilized to model the interaction between the base station (BS) and users. The revenue maximization problem of the BS is first converted to rate allocation problem, then the optimal rate allocation for each user is obtained by variable substitution. Finally, a price-based power allocation with rate proportional fairness (PAPF) algorithm is proposed based on the relationship between rate and transmit power. Simulation results show that the proposed PAPF algorithm is superior to the previous price-based power allocation algorithm in terms of fairness index and minimum normalized user (MNU) rate.

This paper proposes a new user association method to maximize the downlink system throughput in a cellular network, where the system throughput is defined based on (p,α)-proportional fairness. The proposed method assumes a fully decentralized approach, which is practical in a real system as complicated inter-base station (BS) cooperation is not required. In the proposed method, each BS periodically and individually broadcasts supplemental information regarding its bandwidth allocation to newly connected users. Assisted by this information, each user calculates the expected throughput that will be obtained by connecting to the respective BSs. Each user terminal feeds back the metric for user association to the temporally best BS, which represents a relative increase in throughput through re-association to that BS. Based on the reported metrics from multiple users, each BS individually updates the user association. The proposed method gives a general framework for optimal user association for (p,α)-proportional fairness-based system throughput maximization and is especially effective in heterogeneous cellular networks where low transmission-power pico BSs overlay a high transmission-power macro BS. Computer simulation results show that the proposed method maximizes the system throughput from the viewpoint of the given (p,α)-proportional fairness.

In satellite/terrestrial integrated mobile communication systems (STICSs), a user terminal directly connects both terrestrial and satellite base stations. STICS enables expansion of service areas and provides a robust communication service for large disasters. However, the cell radius of the satellite system is large (approximately 100km), and thus a capacity enhancement of the satellite subsystem for accommodating many users is needed. Therefore, in this paper, we propose an application of two methods — multiple-input multiple-output (MIMO) transmission using multi-satellites and non-orthogonal multiple access (NOMA) for STICS — to realize the performance improvement in terms of system capacity and user fairness. Through numerical simulations, we show that system capacity and user fairness are increased by the proposed scheme that applies the two methods.

This paper investigates the system-level throughput of non-orthogonal multiple access (NOMA) with a successive interference canceller (SIC) in the cellular downlink assuming proportional fair (PF)-based radio resource (bandwidth and transmission power) allocation. The purpose of this study is to examine the possibility of applying NOMA with a SIC to the systems beyond the 4G cellular system. Both the mean and cell-edge user throughput are important in a real system. PF-based scheduling is known to achieve a good tradeoff between them by maximizing the product of the user throughput among users within a cell. In NOMA with a SIC, the scheduler allocates the same frequency to multiple users simultaneously, which necessitates multiuser scheduling. To achieve a better tradeoff between the mean and cell-edge user throughput, we propose and compare three power allocation strategies among users, which are jointly implemented with multiuser scheduling. Extensive simulation results show that NOMA with a SIC with a moderate number of non-orthogonally multiplexed users significantly enhances the system-level throughput performance compared to orthogonal multiple access (OMA), which is widely used in 3.9 and 4G mobile communication systems.

To improve the data rate in OFDMA-based wireless networks, Carrier Aggregation (CA) technology has been included in the LTE-Advanced standard. Different Carrier Component (CC) capacities of users under the same eNodeB (eNB, i.e. Base Station) make it challenging to allocate resources with CA. In this paper, we jointly consider CC and Resource Block (RB) assignments, and power allocation to achieve proportional fairness in the long term. The goal of the problem is to maximize the overall throughput with fairness consideration. We consider a more general CC assignment framework that each User Equipment (UE) (i.e. Mobile Station) can support any number of CCs. Furthermore, we have proved the problem is NP-hard, even if power is equally allocated to RBs. Thus, first an optimal RB assignment and power allocation algorithm is proposed and then a carrier aggregation enabled joint resource allocation algorithm called CARA is proposed. By jointly considering CC and RB assignments, and power allocation, the proposed approach can achieve better performance. Simulation results show the proposed algorithm can significantly improve performance, e.g., total throughput compared with the existing algorithm.

Scheduling restriction is attracting much attention in LTE-Advanced as a technique to reduce the power consumption and network overheads in interference coordinated heterogeneous networks (HetNets). Such a network with inter-cell interference coordination (ICIC) provides two radio resources with different channel quality statistics. One of the resources is protected (unprotected) from inter-cell interference (hence, called protected (non-protected) resource) and has higher (lower) average channel quality. Without scheduling restriction, the channel quality feedback would be doubled to reflect the quality difference of the two resources. We present a simple scheduling restriction scheme that addresses the problem without significant performance degradation. Users with relatively larger (smaller) average channel quality difference between the two resources are scheduled in the protected (non-protected) resource only, and a boundary user, determined by a proportional fair resource allocation (PFRA) under simplified static channels, is scheduled on one of the two resources or both depending on PFRA. Having most users scheduled in only one of the resources, the power consumption and network overheads that would otherwise be required for the channel quality feedback on the other resource can be avoided. System level simulation of LTE-Advanced downlink shows that the performance degradation due to our scheduling restriction scheme is less than 2%, with the average feedback reduction of 40%.

The important issue of an adaptive scheduling scheme is to maximize throughput while providing fair services to all users, especially under strict quality of service requirements. To achieve this goal, we consider the problem of multiuser scheduling under a given fairness constraint. A novel Adaptive Fairness and Throughput Control (AFTC) approach is proposed to maximize the network throughput while attaining a given min-max fairness index. Simulation results reveal that comparing to straightforward methods, the proposed AFTC approach can achieve the desired fairness while maximizing the throughput with short convergence time, and is stable in dynamic scenarios. The trade-off between fairness and throughput can be accurately controlled by adjusting the scheduler's parameters.

Orthogonal frequency division multiple access (OFDMA) is adopted as a multiuser access scheme in recent cellular systems such as long term evolution (LTE) and WiMAX. In those systems, the performance improvement on cell-edge users is crucial to provide high-speed services. We propose a new resource allocation scheme based on multiple input multiple output – orthogonal frequency division multiple access – code division multiplexing (MIMO-OFDMA-CDM) to achieve performance improvements in terms of cell-edge user throughput, bit error rate, and fairness among users. The proposed scheme adopts code division multiplexing for MIMO-OFDMA and a modified proportional fairness algorithm for CDM, which enables the fairness among users and a higher throughput. The performance improvements are clarified by theoretical analysis and simulations.

A modified proportional fairness (PF) scheduling scheme for OFDMA systems with imperfect channel quality indicator is suggested. It is based on user grouping, and in system level simulations, the proposed scheme improves average user throughput considerably when compared to conventional PF scheduling without grouping.

This letter introduces a new fairness concept, namely proportional quasi-fairness and proves that the optimal end-to-end rate of a network utility maximization can be proportionally quasi-fair with a properly chosen network utility function for an arbitrary compact feasible set.

In this paper, we mathematically derive a matrix-form solution named resource allocation matrix (RAM) for sub-band allocation in an orthogonal frequency division multiple access (OFDMA) system. The proposed scheme is designed to enhance throughput under a strict user fairness condition such that every user has an equal number of sub-bands per frame. The RAM designates the most preferable sub-band for every user. The proposed scheme is evaluated in terms of throughput and user fairness by comparison with the proportional fairness (PF) scheme and greedy scheme. Numerical results show that the proposed scheme has overwhelming superiority to other schemes in terms of fairness and tight competitive in terms of throughput.

The biggest challenge in multi-cell MIMO multiplexing systems is how to effectively suppress the other-cell interference (OCI) since the OCI severely decrease the system performance. Cooperation among cells is one of the most promising solutions to OCI problems. However, this solution suffers greatly from delay and overhead issues, which make it impractical. A coordinated MIMO system with a simplified cooperation between the base stations is a compromise between the theory and practice. We aim to devise an effective resource allocation algorithm based on a coordinated MIMO system that largely alleviates the OCI. In this paper, we propose a joint resource allocation algorithm incorporating intra-cell beamforming multiplexing and inter-cell interference suppression, which adaptively allocates the transmitting power and schedules users while achieving close to an optimal system throughput under proportional fairness consideration. We formulate this problem as a nonlinear combinational optimization problem, which is hard to solve. Then, we decouple the variables and transform it into a problem with convex sub-problems that can be solve but still need heavy computational complexity. In order to implement the algorithm in real-time scenarios, we reduce the computational complexity by assuming an equal power allocation utility to do user scheduling before the power allocation. Extensive simulation results show that the joint resource allocation algorithm can achieve a higher throughput and better fairness than the traditional method while maintains the proportional fairness. Moreover, the low-complexity algorithm obtains a better fairness and less computational complexity with only a slight loss in throughput.

Proportional fair scheduling attains a graceful trade-off between fairness among users and total system throughput. It is simple to implement in single carrier transmission systems, while changes to a prohibitively complex combinatorial problem for multi-carrier transmission systems. This letter addresses a couple of conditions that approximate multi-carrier proportional fair scheduling (MCPF) as carrier-by-carrier proportional fair scheduling (CCPF), which has much lower complexity than MCPF. Numerical results show that the proportional fairness metric of CCPF approaches to that of MCPF for those conditions.

This paper considers the proportional fair (PF) based subcarrier allocation problem in a multihop orthogonal frequency division multiple access (OFDMA) broadcast system with decode-and-forward (DF) relays. The problem is formulated as a mixed binary integer programming problem with the objective to achieve proportional fairness among users and exploit the diversity provided by the independent frequency selective fading among hops. Since it is prohibitive to find the optimal solution, two efficient heuristic schemes are proposed. Simulation results indicate that with the same fairness performance, the proposed schemes achieve considerable capacity gain over the conventional PF scheduling method.

In this paper, we propose a scheme of frequency sub-band allocation to obtain maximum throughput in an orthogonal frequency division multiple access (OFDMA) system where each user has a finite number of packets to transmit, which are generated from packet calls with arbitrary size and arbitrary arrival rate. The proposed scheme is evaluated in terms of throughput and user fairness in comparison with the proportional fairness (PF) scheme and the Greedy scheme under the finite queue length condition. Numerical results show that the proposed scheme is superior to the Greedy scheme in terms of both throughput and fairness for finite queue length.

We have developed a novel downlink packet scheduling scheme for a multiuser OFDMA system in which a subchannel can be time-multiplexed among multiple users. This scheme which is called Matrixed-based Proportional Fairness can provide a high system throughput while ensuring fairness. The scheme is based on a Proportional Fairness (PF) utility function and can be applied to any of the PF-based schedulers. Our scheduler explores multichannel multiuser diversity by using a two-dimensional matrix combining user selection, subchannel assignment, and time slot allocation. Furthermore, unlike other PF-based schemes, our scheme considers finitely backlogged queues during the time slot allocation. By doing so, it can exploit multichannel multiuser diversity to utilize bandwidth efficiently and with throughput fairness. Additionally, fairness in the time domain is enhanced by limiting the number of allocated time slots. Intensive simulations considering finitely backlogged queues and user mobility prove the scheme's effectiveness.