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.

A simple robust finite-time convergent observer is presented in the presence of unknown input disturbance and measurement noise. In order to achieve the robust estimation and ensure the finite-time convergence, the proposed observer is constructed by using a multiple integral observer scheme in a hybrid system framework. Comparative computer simulations and laboratory experiments have been performed to test the effectiveness of the proposed observer.

Power-aware distributed file systems for efficient Big Data processing are increasingly moving towards power-proportional designs. However, current data placement methods for such systems have not given careful consideration to the effect of gear-shifting during operations. If the system wants to shift to a higher gear, it must reallocate the updated datasets that were modified in a lower gear when a subset of the nodes was inactive, but without disrupting the servicing of requests from clients. Inefficient gear-shifting that requires a large amount of data reallocation greatly degrades the system performance. To address this challenge, this paper proposes a data placement method known as Accordion, which uses data replication to arrange the data layout comprehensively and provide efficient gear-shifting. Compared with current methods, Accordion reduces the amount of data transferred, which significantly shortens the period required to reallocate the updated data during gear-shifting then able to improve the performance of the systems. The effect of this reduction is larger with higher gears, so Accordion is suitable for smooth gear-shifting in multigear systems. Moreover, the times when the active nodes serve the requests are well distributed, so Accordion is capable of higher scalability than existing methods based on the I/O throughput performance. Accordion does not require any strict constraint on the number of nodes in the system therefore our proposed method is expected to work well in practical environments. Extensive empirical experiments using actual machines with an Accordion prototype based on the Hadoop Distributed File System demonstrated that our proposed method significantly reduced the period required to transfer updated data, i.e., by 66% compared with an existing method.

In elevator-group control, the average number of running cars should be finely adjusted by the dynamically controlling the number of running cars (DCNRC). Traffic demand in an office building varies throughout the day. In this paper, we propose a new energy-saving method for elevator-group control that adjusts the number of running cars according to the traffic demand, simulate the proposed energy-saving method under nearly real traffic demand conditions of an office building, and reduce the daily energy consumption to the target level after several days.

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.

Energy-aware distributed file systems are increasingly moving toward power-proportional designs. However, current works have not considered the cost of updating data sets that were modified in a low-power mode, where a subset of nodes were powered off. In detail, when the system moves to a high-power mode, it must internally replicate the updated data to the reactivated nodes. Effectively reflecting the updated data is vital in making a distributed file system, such as the Hadoop Distributed File System (HDFS), power proportional. In the current HDFS design, when the system changes power mode, the block replication process is ineffectively restrained by a single NameNode because of access congestion of the metadata information of blocks. This paper presents a novel architecture, a NameNode and DataNode Coupling Hadoop Distributed File System (NDCouplingHDFS), which effectively reflects the updated blocks when the system goes into high-power mode. This is achieved by coupling metadata management and data management at each node to efficiently localize the range of blocks maintained by the metadata. Experiments using actual machines show that NDCouplingHDFS is able to significantly reduce the execution time required to move updated blocks by 46% relative to the normal HDFS. Moreover, NDCouplingHDFS is capable of increasing the throughput of the system supporting MapReduce by applying an index in metadata management.

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.

In cloud computing, multiple users coexist in one datacenter infrastructure and the network is always shared using VMs. Network bandwidth allocation is necessary for security and performance guarantees in the datacenter. InfiniBand (IB) is more widely applied in the construction of datacenter cluster and attracts more interest from the academic field. In this paper, we propose an IB dynamic bandwidth allocation mechanism IBShare to achieve different Weight-proportional and Min-guarantee requirements of allocation entities. The differentiated IB Congestion Control (CC) configuration is proven to offer the proportional throughput characteristic at the flow level. IBShare leverages distributed congestion detection, global congestion computation and configuration to dynamically provide predictable bandwidth division. The real IB experiment results showed IBShare can promptly adapt to the congestion variation and achieve the above two allocation demands through CC reconfiguration. IBShare improved the network utilization than reservation and its computation/configuration overhead was low.

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.

When computing resources are consolidated in a few huge data centers, a massive amount of data is transferred to each data center over a wide area network (WAN). This results in increased power consumption in the WAN. A distributed computing network (DCN), such as a content delivery network, can reduce the traffic from/to the data center, thereby decreasing the power consumed in the WAN. In this paper, we focus on the energy-saving aspect of the DCN and evaluate its effectiveness, especially considering traffic locality, i.e., the amount of traffic related to the geographical vicinity. We first formulate the problem of optimizing the DCN power consumption and describe the DCN in detail. Then, numerical evaluations show that, when there is strong traffic locality and the router has ideal energy proportionality, the system's power consumption is reduced to about 50% of the power consumed in the case where a DCN is not used; moreover, this advantage becomes even larger (up to about 30%) when the data center is located farthest from the center of the network topology.

In this paper, the resource allocation problem for proportional fairness in hybrid Cognitive Radio (CR) systems is studied. In OFDMA-based CR systems, traditional resource allocation algorithms can not guarantee proportional rates among CR users (CRU) in each OFDM symbol because the number of available subchannels might be smaller than that of CRUs in some OFDM symbols. To deal with this time-varying nature of available spectrum resource, a hybrid CR scheme in which CRUs are allowed to use subchannels in both spectrum holes and primary users (PU) bands is adopted and a resource allocation algorithm is proposed to guarantee proportional rates among CRUs with no undue interference to PUs.

This paper examines the robust performance of a load torque observer for the position control of a surface-mounted permanent magnet synchronous motor (PMSM) under parameter uncertainties. The load torque observer has been widely employed to compensate for unknown slow-varying disturbances without explicit analysis on the robustness against parameter uncertainties. By using the singular perturbation theory this paper presents an analysis on the robust performance of the load torque observer based on the reduced-order estimator. As the observer poles are placed sufficiently left of the complex plane, the feedforward compensation with estimation can recover nominal system performance without parameter uncertainties and load torque disturbance. An example shows the performance of the load torque observer.

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.