Bandwidth aggregation (BAG) techniques have been researched for many years in an efforts to enhance throughput for multi-homed streaming service. However, despite of the considerable attention being devoted towards energy-efficient communications, the power efficiency for BAG has not been considered yet. To improve the power efficiency in multi-homed streaming service, this paper proposes Power Minimized Rate Allocation Scheme (PMRAS) with optimal rate allocation at each interface while guaranteeing an allowable packet loss rate. In developing PMRAS, we first formulate a power consumption model based on the network interface state (i.e. active and idle state). We adopt a Lagrangian algorithm to solve the convex optimization problem of power consumption. The performance results gained from a numerical analysis and simulations (NS-2) reveal that the proposed scheme offers superior performance over the existing rate allocation scheme for BAG with guaranteed required quality of service.

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.

Nowadays, with spreads of inexpensive small communication devices, a number of wireless local area networks (WLANs) have been deployed even in the same building for the Internet access services. Their wireless access-points (APs) are often independently installed and managed by different groups such as departments or laboratories in a university or a company. Then, a user host can access to multiple WLANs by detecting signals from their APs, which increases the energy consumption and the operational cost. It may also degrade the communication performance by increasing interferences. In this paper, we present an AP aggregation approach to solve these problems in multiple WLAN environments by aggregating deployed APs of different groups into limited ones using virtual APs. First, we formulate the AP aggregation problem as a combinatorial optimization problem and prove the NP-completeness of its decision problem. Then, we propose its heuristic algorithm composed of five phases. We verify the effectiveness through extensive simulations using the WIMNET simulator.

LTE-Advanced supports asymmetric carrier aggregation (CA) to achieve flexible bandwidth allocation by applying different numbers of component carriers (CCs) between the downlink and uplink. This paper experimentally clarifies the achievable downlink throughput performance when uplink control information (UCI) feedback mechanism using the physical uplink shared channel (PUSCH), which enables minimization of the UCI overhead while maintaining the required reception quality, is applied in asymmetric CA. The laboratory experimental results show that the stable reception quality control of the channel quality information (CQI) with the target block error rate (BLER) of 10-1 to 10-2 is achieved irrespective of the average received signal-to-noise power ratio (SNR) when the control offset parameter of approximately 1.25 is used. We also show that the achievable downlink throughput when the CQI error is considered is almost the same as that in no CQI error case. Furthermore, based on the experimental results in a real field environment, a suburban area of Yokosuka city in Japan, we confirm stable adaptive modulation and coding (AMC) operation including target BLER control of the CQI on the PUSCH in asymmetric CA. The field experimental results also show that when CA with 5 CCs (90-MHz bandwidth) and 2-by-2 rank-2 multiple-output multiple-input (MIMO) multiplexing are employed in the downlink, the peak throughput of approximately 640Mbps is achieved even considering the CQI error.

Bandwidth expansion in Long Term Evolution (LTE)-Advanced is supported via carrier aggregation (CA), which aggregates multiple component carriers (CCs) to accomplish very high data rate communications. Heterogeneous networks (HetNets), which set pico-base stations in macrocells are also a key feature of LTE-Advanced to achieve substantial gains in coverage and capacity compared to macro-only cells. When CA is applied in HetNets, transmission on all CCs may not always be the best solution due to the extremely high levels of inter-cell interference experienced by HetNets. Activated CCs that are used for transmission should be selected depending on inter-cell interference conditions and the traffic offered in the cells. This paper presents a scheme to select CCs through centralized control assuming a centralized baseband unit (C-BBU) configuration. A C-BBU involves pooling tens or hundreds of baseband resources where one baseband resource can be connected to any CC installed in remote radio heads (RRHs) via optical fibers. Fewer baseband resources can be prepared in a C-BBU than those of CCs in RRHs to reduce the cost of equipment. Our proposed scheme selects the activated CCs by considering the user equipment (UE) assigned to CCs under the criterion of maximizing the proportional fairness (PF) utility function. Convex optimization using the Karush-Kuhn-Tucker (KKT) conditions is applied to solve the resource allocation ratio that enables user throughput to be estimated. We present results from system level simulations of the downlink to demonstrate that the proposed algorithm to select CCs can outperform the conventional one that selects activated CCs based on the received signal strength. We also demonstrate that our proposed algorithm to select CCs can provide a good balance in traffic load between CCs and achieve better user throughput with fewer baseband resources.

This paper evaluates the downlink performance of an LTE-Advanced (LTE-A) heterogeneous network that uses carrier aggregation (CA) between macro and small cells. The concept of utilizing the CA functionalities in LTE-A is effective in increasing the network capacity in a congested area through raising of the base station density using small cells overlaid onto an existing macro cell network. This concept is also effective in maintaining the mobility performance of user equipment (UE) because handover operation is not applied when entering/leaving a small cell, but component carrier addition/removal is only performed through CA while maintaining the connection to a macro cell. In order to present comprehensive performance evaluations in an LTE-A heterogeneous network with CA, this paper evaluates various performance criteria, e.g., downlink cell throughput and downlink user throughput. According to the obtained simulation results, the total downlink cell throughput achieved in an LTE-A heterogeneous network deployment with CA (four small cells overlaid onto a macro cell sector) exhibits a 3.9-fold improvement compared to a conventional-macro-cell-only network deployment using two frequency bands.

In this paper, we propose a novel in-network aggregation scheduling scheme for forest fire monitoring in a wireless sensor network. This adaptively configures both the timeout and the collecting period according to the potential level of a fire occurrence. At normal times, the proposed scheme decreases a timeout that is a wait time for packets sent from child nodes and makes the collecting period longer. That reduces the dissipated energy of the sensor node. Conversely, the proposed scheme increases the timeout and makes the collecting period shorter during fire occurrences in order to achieve more accurate data aggregation and early fire detection.

A receiver architecture and a digital IQ imbalance compensation method for dual-carrier reception are newly proposed. The impact of IQ imbalance on the baseband signal is mathematically analyzed. Based on the analysis, IQ imbalance parameters are estimated and the coupling effect of IQ imbalance is compensated using digital baseband processing alone. Simulation results show that the proposed IQ imbalance compensation successfully removes IQ imbalance. The deviation from the ideal performance is less than 1 dB when it is applied to the 3GPP-LTE carrier aggregation.

This paper proposed three channel aggregation schemes for cognitive radio networks, a constant channel aggregation scheme, a probability distribution-based variable channel aggregation scheme, and a residual channel-based variable channel aggregation scheme. A cognitive radio network can have a wide bandwidth if unused channels in the primary networks are aggregated. Channel aggregation schemes involve either constant channel aggregation or variable channel aggregation. In this paper, a Markov chain is used to develop an analytical model of channel aggregation schemes; and the performance of the model is evaluated in terms of the average sojourn time, the average throughput, the forced termination probability, and the blocking probability. Simulation results show that channel aggregation schemes can reduce the average sojourn time of cognitive users by increasing the channel occupation rate of unused channels in a primary network.

It is important to optimize aggregation schemes for heterogeneous wireless networks for maximizing communication throughput utilizing any available radio access networks. In the heterogeneous networks, differences of the quality of service (QoS), such as throughput, delay and packet loss rate, of the networks makes difficult to maximize the aggregation throughput. In this paper, we firstly analyze influences of such differences in QoS to the aggregation throughput, and show that it is possible to improve the throughput by adjusting the parameters of an aggregation system. Since manual parameter optimization is difficult and takes much time, we propose an autonomous parameter tuning scheme using a machine learning algorithm for the heterogeneous wireless network aggregation. We implement the proposed scheme on a heterogeneous cognitive radio network system. The results on our experimental network with network emulators show that the proposed scheme can improve the aggregation throughput better than the conventional schemes. We also evaluate the performance using public wireless network services, such as HSDPA, WiMAX and W-CDMA, and verify that the proposed scheme can improve the aggregation throughput by iterating the learning cycle even for the public wireless networks. Our experimental results show that the proposed scheme achieves twice better aggregation throughput than the conventional schemes.

For large-scale sensor networks, multiple sinks are often deployed in order to reduce source-to-sink distance and thus cost of data delivery. However, having multiple sinks may work against cost reduction, because routes from sources can diverge towards different sinks which reduces the benefit of in-network data aggregation. In this letter we propose a self-clustering data aggregation protocol (SCAP) that can benefit from having multiple sinks as well as joint routes. In SCAP, nodes which detect the event communicate with each other to aggregate data between themselves, before sending the data to the sinks. The self-clustering extends network lifetime by reducing energy consumption of nodes near the sinks, because the number of paths in which the packets are delivered is reduced. A performance comparison with existing protocols L-PEDAP and LEO shows that SCAP can conserve energy and extend network lifetime significantly, in a multi-sink environment.

We propose a novel query-dependent feature aggregation (QDFA) method for medical image retrieval. The QDFA method can learn an optimal feature aggregation function for a multi-example query, which takes into account multiple features and multiple examples with different importance. The experiments demonstrate that the QDFA method outperforms three other feature aggregation methods.

Since wireless sensor networks (WSNs) are resources-constrained, it is very essential to gather data efficiently from the WSNs so that their life can be prolonged. Data aggregation can conserve a significant amount of energy by minimizing transmission cost in terms of the number of data packets. Many applications require privacy and integrity protection of the sampled data while they travel from the source sensor nodes to a data collecting device, say a query server. However, the existing schemes suffer from high communication cost, high computation cost and data propagation delay. To resolve the problems, in this paper, we propose a new and efficient integrity protecting sensitive data aggregation scheme for WSNs. Our scheme makes use of the additive property of complex numbers to achieve sensitive data aggregation with protecting data integrity. With simulation results, we show that our scheme is much more efficient in terms of both communication and computation overheads, integrity checking and data propagation delay than the existing schemes for protecting integrity and privacy preserving data aggregation in WSNs.

One of the most challenging issues in wireless sensor networks is extension of the overall network lifetime. Data aggregation is one promising solution because it reduces the amount of network traffic by eliminating redundant data. In order to aggregate data, each sensor node must temporarily store received data, which requires a specific amount of memory. Most sensor nodes use static random access memory (SRAM) or flash memory for storage. SRAM can be implemented in a one-chip sensor node at low cost; however, SRAM requires standby energy, which consumes a lot of power, especially because the sensor node spends most of its time sleeping, i.e. its radio circuits are quiescent. This study proposes two types of divided SRAM: equal-size divided SRAM and equal-ratio divided SRAM. Simulations show that both proposed SRAM types offer reduced power consumption in various situations.

Carrier aggregation (CA) is one of the most important techniques for LTE-Advanced because of its capability to support a wide transmission bandwidth of up to 100 MHz and heterogeneous networks effectively while achieving backward compatibility with the Release 8 LTE. In order to improve the performance of control information transmission in heterogeneous networks, cross-carrier scheduling is supported, i.e., control information on one component carrier (CC) can assign radio resources on another CC. To convey the control information efficiently, a search space is defined and used in Release 8 LTE. In cross-carrier scheduling, the optimum design for the search space for different CCs is a paramount issue. This paper presents two novel methods for search space design. In the first method using one hash function, a user equipment (UE)-specific offset is introduced among search spaces associated with different CCs. Due to the UE-specific offsets, search spaces of different UEs are staggered and the probability that the search space of one UE is totally overlapped by that of another UE can be greatly reduced. In the second method using multiple hash functions, a novel randomization scheme is proposed to generate independent hash functions for search spaces of different CCs. Because of the perfect randomization effect of the proposed method, search space overlapping of different UEs is reduced. Simulation results show that both the proposed methods effectively reduce the blocking probability of the control information compared to existing methods.

In Long-Term Evolution-Advanced (LTE-A), which is currently in the process of standardization in the 3rd generation partnership project (3GPP), carrier aggregation (CA) was introduced as a main feature for bandwidth extension while maintaining backward compatibility with LTE Release 8 (Rel. 8). In the CA mode of operation, since two or more component carriers (CCs), each of which is compatible with LTE Rel. 8, are aggregated, mobility management is needed for CCs such as inter/intra-frequency handover, CC addition, and CC removal to provide sufficient coverage and better overall signal quality. Therefore, the signaling overhead for Radio Resource Control (RRC) reconfiguration for the mobility management of CCs in LTE-A is expected to be larger than that in LTE Rel. 8. In addition, CA allows aggregation of cells with different types of coverage. Therefore, the signaling overhead may be dependent on the coverage of each CC assumed in a CA deployment scenario. Furthermore, especially in a picocell-overlaid scenario, the amount of signaling overhead may be different according to whether the aggregation of CCs between a macrocell and a picocell, i.e., transmission and reception from multiple sites, is allowed or not. Therefore, this paper investigates the CC control overhead with several CC management policies in some CA deployment scenarios, including a scenario with overlaid picocells. Simulation results show that the control overhead is almost the same irrespective of the different management policies, when almost the same coverage is provided for the CCs. In addition, it is shown that the increase in the control overhead is not significant even in a CA deployment scenario with overlaid picocells. We also show that the amount of signaling overhead in a picocell-overlaid scenario with the CA between a macrocell and a picocell is almost twice as that without the CA between a macrocell and a picocell.

This letter investigates the cluster lifetime of single-hop wireless sensor networks with cooperative Multi-Input Single-Output (MISO) scheme. The energy consumptions of both intra-cluster and out-cluster communications are considered. Moreover, uniform and linear data aggregations are discussed. It is found the optimal transmission scheme varies with the distance from the cluster to the base station. More interestingly and novelly, the effect of cluster size on the cluster lifetime has been clarified.

Wireless Sensor Networks (WSNs) rely on in-network aggregation for efficiency, that is, readings from sensor nodes are aggregated at intermediate nodes to reduce the communication cost. However, the previous optimally secure in-network aggregation protocols against multiple corrupted nodes require two round-trip communications between each node and the base station, including the result-checking phase whose congestion is O(log n) where n is the total number of sensor nodes. In this paper, we propose an efficient and optimally secure sensor network aggregation protocol against multiple corrupted nodes by a random-walk adversary. Our protocol achieves one round-trip communication to satisfy optimal security without the result-checking phase, by conducting aggregation along with the verification, based on the idea of TESLA technique. Furthermore, we show that the congestion complexity, communication complexity and computational cost in our protocol are constant, i.e., O(1).

The design of an energy-efficient wavelength division multiplexing (WDM) transponder is proposed and effectiveness of the proposed WDM transponder is experimentally studied. The proposed WDM transponder interworking with the link-aggregation technique possessed by a layer 2 switch can achieve power saving depending on traffic volume variations by utilizing an adaptive interface control. Monitoring methods for the link connectivity of a sleep link are also discussed.

The Internet is an extremely convenient network and has become one of the key infrastructures for daily life. However, it suffers from three serious problems; its structure does not suit traffic centralization, its power consumption is rapidly increasing, and its round-trip time (RTT) and delay jitter are large. This paper proposes an extremely energy efficient layer-3 network architecture for the future Internet. It combines the Service Cloud with the Cloud Router and application servers, with the Optical Aggregation Network realized by optical circuit switches, wavelength-converters, and wavelength-multiplexers/demultiplexers. User IP packets are aggregated and transferred through the Optical Aggregation Network to Cloud transparently. The proposed network scheme realizes a network structure well suited to traffic centralization, reduces the power consumption to 1/20-1/30 compared to the existing Internet, reduces the RTT and delay jitter due to its simplicity, and offers easy migration from the existing Internet.