A great amount of research has devoted to cognitive radio (CR) in recent years in order to improve spectrum efficiency. In decentralized CR networks, it is not realistic for CR users to sense entire spectrum in practice due to hardware limitations. Consequently, the partially observable Markov decision process (POMDP) can be utilized to provide CR users with sufficient information in partially observable environments. Existing POMDP-based protocols adopt channel aggregation techniques in order to improve spectrum opportunities and system performance. However, the required time for channel sensing is neglected which can result in large sensing time overhead and spectrum opportunity loss in realistic environments. In this paper, based on partially observable channel state with the consideration of sensing overhead, the stochastic multiple channel sensing (SMCS) protocol is proposed to conduct optimal channel selection for maximizing the aggregated throughput of CR users. By adopting the proposed SMCS protocol, CR users can highly accommodate themselves to rapidly varying environment based on the dynamically adjustable channel sensing strategy. Moreover, the channel sensing problem is further extended to imperfect sensing scenario, which can severely degrade system throughput due to packet collision between primary users (PUs) and CR users. Consequently, in addition to channel selection, it is required for CR users to determine the sensing time length in order to address the collision problem. The two-phase SMCS (TSMCS) protocol is proposed to maximize the aggregated throughput of CR users while still fulfilling PUs' quality-of-service (QoS) requirements. Numerical results show that the proposed SMCS and TSMCS protocols can effectively maximize the aggregated throughput for decentralized CR networks.

The deployment of small cells with carrier aggregation (CA) technique is a significant feature of next-generation cellular networks. The potential benefits of dense base stations (BSs) deployment are provided by using proper interference management mechanisms. Meanwhile, the user equipments (UEs) can simultaneously access multiple component carriers (CCs) to meet the dramatically increased traffic demand by means of CA. In this paper, an optimization problem consists of UE-BS association, CC configuration, frequency resources scheduling, and power allocation with adaptive modulation schemes is investigated to enhance energy efficiency, focusing on the quality of service (QoS)-aware CA. To obtain the near optimal solutions as well as the consideration of computational complexity, a cross entropy- based algorithm (CEA) is proposed to jointly solve the combinatorial problem. Compared to the traditional heuristic algorithms, the merits of proposed scheme can be observed via simulation results.

In this paper, we consider a flexibility and efficiency problem with DLMS automatic reading smart meter system. We introduce a two-tier hierarchy structure with concentrator. Our proposed concentrator model simply extended the power of Device Language Message Specification (DLMS) protocol. The result is then used to make the two-tier hierarchy available. Compared to origin DLMS protocol, our model supports at most 65536 smart meters rather than 256. Our work may be applied to the newest Advanced Metering Infrastructure (AMI) research.

In 3GPP Release-12 specification, the adoption of small cells in long term evolution (LTE) networks is considered as a promising solution to meet the growing traffic demand for mobile data usage. However, energy consumption becomes a crucial challenge for network operators to deploy more small cells in heterogeneous networks in order to fulfill the requirement for achieving high data rates. In this paper, an advanced signaling mechanism has been proposed to practically acquire global channel state information (CSI) between network components. Based on the signaling scheme, an energy-efficient cell selection and resource allocation (ECR) algorithm is proposed to increase system energy efficiency by handovering UEs from light-loaded base station to nearby cells. Some active cells can therefore be switched off to reduce total energy consumption. Simulation results show that better energy efficiency can be achieved by adopting the proposed signaling and ECR schemes.

Recently, promoting energy efficiency is an important research issue in the wireless communication system. This paper investigates the resource management problem with the regularized zero-forcing (RZF) precoding for the distributed large-scale multiple-input multiple-output cloud radio access network (DLS MIMO C-RAN) which consists of a large number of spatially distributed remote radio heads (RRHs). The challenges of this power allocation problem arise from the presence of both interference and imperfect channel state information at the transmitter (CSIT). Therefore, the C-RAN based power allocation schemes are designed to efficiently allocate the transmit power of each RRH. Moreover, the large random matrix theory is applied to derive the asymptotic expressions for large number of antennas. Simulation results show that the proposed schemes can provide better energy efficiency with the consideration of quality-of-service (QoS) support.

Because of the scarcity of spectrum and energy resource, the problems about allocation of these resources become more and more important in recent years. However, inappropriate resource allocation may bring about high intercell interference which has a great effect on the performance of the entire system. Thus, in this paper, considering inter-cell interference, we provide the optimal formulation of the resource allocation problem and divide it into two sub-problems, including the component carrier (CC) selection problem and the power allocation problem. The proposed enhanced data rate component carrier selection (EDR-CCS) scheme not only reduces the intercell interference but also maximizes the UEs' data transmission rates. Regarding the power allocation problem, two schemes (i.e., geometry programming power allocation (GPPA) and constant interference power allocation (CIPA)) are proposed with the target of finding suboptimal solutions to the power allocation problem under the constraints of eNB's maximum transmission power and UEs' transmission rate requirement on the control channel of primary CC (PCC). Simulation results demonstrate that the data rate performance of EDR-CCS scheme is better than that of random CC selection scheme. Furthermore, GPPA scheme can achieve better performance than CIPA scheme since the GPPA scheme can accommodate the variations from inter-cell interference.

ABSTRACT Multicarrier code division multiple access (MC‐CDMA), is a promising multiplexing technique for future communication systems. In this study, we employ the well‐known Walsh‐Hadamard spreading codes for synchronous downlink transmission of MC‐CDMA systems. The spreading codes allow that the frequency diversity to be efficiently exploited. However, multipath propagation may cause orthogonality among users is distorted, and this distortion produces multiple access interference (MAI). To eliminate this effect, we propose a pre‐filtering‐based MC‐CDMA system which uses a pre‐filtering technique at the transmitter and an equal gain combining (EGC) scheme at the receivers, respectively. Our proposed pre‐filtering technique transforms the transmitted signals so that the MAI can be eliminated, and the EGC scheme weights the signals received from all subcarriers so that channel distortions can be compensated. Furthermore, the proposed technique can calculate the transmitted power over all subcarriers to satisfy the required quality of service of each user and archive MAI‐free. In this paper, performance in terms of bit error rate is analyzed; in comparison with the EGC, orthogonal restoring combining, and maximal ratio combining schemes at receiver, respectively. Copyright © 2011 John Wiley & Sons, Ltd.

This paper studies the joint resource allocation problem of antenna, subchannel, transmission power, and phase duration for the relay-enhanced bidirectional multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) networks. The goal of resource allocation is to minimize the transmission energy in the networks with multiple relay stations (RSs) under the data rate constraints of user equipment (UE). The challenges of this resource allocation problem arise from the complication of multiple-phase assignments within a subchannel since the RS can provide an additional transmission path from the base station to the UEs. The green resource allocation (GRA) schemes with reduced computational complexity are proposed in this paper to develop the joint resource allocation algorithm for the UEs with the consideration of direct and two-hop communications. Both the separate downlink (DL) and uplink (UL) and mixed DL and UL relaying assignments are adopted to obtain the solutions for proposed GRA schemes. Simulation results show that the GRA schemes can provide comparably better energy conservation with the consideration of quality-of-service (QoS) support.

Relay nodes (RN) have been suggested to be placed near the edge of a cellular network in order to improve link qualities of cell edge user equipments (UEs). Compared to conventional homogeneous networks, system performance for the relay-enhanced network can be significantly degraded if handovers between the RNs and evolved node base-station (eNB) are not correctly and immediately determined by the eNB. Therefore, the UEs may suffer from worse channel conditions which can result in increased energy consumption of entire network. In existing long term evolution advanced (LTE-A) standard, fixed reporting time period from the UEs to eNB is considered inflexible which can be too long to provide immediate handover decisions. Hence, prediction-based handover (PH) scheme is proposed to allow eNBs to make potential handover decisions within the UE's reporting period. The channel qualities for both the direct and relay-enhanced links during this period are predicted based on the partially observable Markov decision process. Moreover, three objectives are designed for the proposed PH scheme including maximizing received signal to interference plus noise ratios of UEs, and minimizing system energy consumption without and with considerations of energy outage of relay nodes. Numerical results show that the proposed PH schemes outperform conventional handover scheme from the perspectives of both system energy consumption and outage probability.

It is well known that orthogonal frequency division multiplexing (OFDM) is robust to frequency-selective fading in wireless channels. However, it is sensitive to carrier frequency offset (CFO) which results in inter-carrier interference (ICI) and then degrades the transmission performance significantly. In this paper, a resource allocation scheme for OFDM systems in the presence of ICI is proposed. The aim of the proposed scheme is to maximize the system throughput under a total transmission power constraint. By allocating the resource appropriately, the effect of ICI can be reduced without any ICI cancellation scheme at the receiver, resulting in the increase of system throughput. Numerical results show that the proposed scheme has better throughput as compared to the adaptive subcarrier bandwidth method with equal power allocation or power allocation method with conventional water-filling algorithm.

JPEG2000 is now one of the most promising image compression standards for supporting efficient scalable exchange of large images. Considering Web browsing as a major activity in the Internet, we believe that a large portion of JPEG2000 images would be hosted by Web servers and be retrieved through Internet browsers by means of the hypertext transfer protocol (HTTP). We propose a bandwidth effective streaming mechanism, called BEST, for JPEG2000 images. In addition to providing image streaming, BEST also acts as an efficient and effective traffic shaper/regulator. Through the fragmentation of the JPEG2000 image based on the quality layer of the code-stream, together with the regulation of transmission rates according to the current channel capacity indicated by TCP, BEST achieves streaming of JPEG2000 images through Web browsing and, at the same time, prevents low bit-rate channels from being congested by the instantly exhaustive transmission of JPEG2000 images from Web servers.