This paper proposes a distributed relay and modulation and coding scheme (MCS) selection in wireless cooperative relaying networks where the adaptive modulation and coding (AMC) scheme is applied. First-order finite-state Markov channels (FSMCs) are used to model the wireless channels and make prediction. The objective of the relay policy is to select one relay and MCS among different alternatives in each time-slot according to their channel state information (CSI) with the goal of maximizing the throughput of the whole transmission period. The procedure of relay and MCS selection can be formulated as a discounted Markov decision chain, and the relay policy can be obtained with recent advances in stochastic control algorithms. Simulation results are presented to show the effectiveness of the proposed scheme.

Coordinated multi-point transmission and reception (CoMP) for single user, named as SU-CoMP, is considered as an efficient approach to mitigate inter-cell interference in orthogonal frequency division multiple access (OFDMA) systems. Two prevalent approaches in SU-CoMP are coordinated scheduling (CS) and joint processing (JP). Although JP in SU-CoMP has been proved to achieve a great link performance improvement for the cell-edge user, efficient resource allocation (RA) on the system level is quite needed. However, so far limited work has been done considering JP, and most existing schemes achieved the improvement of cell-edge performance at cost of the cell-average performance degradation compared to the single cell RA. In this paper, a two-phase strategy is proposed for SU-CoMP networks. CS and JP are combined to improve both cell-edge and cell-average performance. Compared to the single cell RA, simulation results demonstrate that, the proposed strategy leads to both higher cell-average and cell-edge throughput.

In this paper, we propose a new modulation classification method based on the combination of clustering and neural network, in which a new algorithm is introduced to extract key features. In order to recognize modulation types based on the constellation diagram such as phase shift keying (PSK) and quadrature amplitude modulation (QAM), fuzzy C-means (FCM) clustering is adopted for recovering the constellation under different number of clusters. Then cluster validity measure is applied to extract key features which discriminate between different modulation types. The features are sent to neural network so that modulation types can be recognized. In order to conquer the disadvantages of standard back propagation (BP) neural network, conjugate gradient learning algorithm of Polak-Ribiere update is employed to improve the speed of convergence and the performance of modulation recognition. Simulation results show that classification rates of the algorithm proposed in this paper are much higher than those of clustering algorithm.

This work investigates a novel semi-blind channel estimation for multiple-input multiple-output (MIMO) space-time block coding (STBC) systems. Algorithms for channel estimation based on whitening-rotation (WR) decomposition that provides a combined quality and spatial scalability is utilized. Using a space-time code-constrained input design, our approach exploits the orthogonality of the signal and noise subspaces in conjunction with orthogonal procrustes (OP) technique to obtain an accurate estimate of the unitary rotation matrix and, consequently, of the channel parameters. Unitary rotation matrices are parameterized a much fewer number of parameters, and signi?cant estimation gains can then be achieved by estimation of such orthogonal matrices. Furthermore, the proposed semi-blind MIMO channel estimation approach is conducted to reduce the complexity of system design when the number of the receive antennas is no less than the number of transmit antennas. Computer simulations are conducted to corroborate the effectiveness of the proposed channel estimation, and they demonstrate the improved performance compared to the existing training-based estimation.

In OFDM-based System such as long term evolution (LTE), the scheduling scheme plays an essential role in not only improving the capacity of system, but also guarantee the fairness among the user equipments (UEs). However, most existing work about scheduling only considers the current throughput in physical layer. Thus in this paper, a cross-layer scheduling with fairness based on restless bandit (CSFRB) scheme with the ‘indexability’ property is proposed for the multi-user orthogonal frequency-division multiplexing (OFDM) system to minimize the distortion in the application layer, to maximize the throughput and to minimize the energy consumption in the physical layer. The scheduling problem is firstly established as a restless bandit problem, which is solved by the primal-dual index heuristic algorithm based on the first order relaxation with low complexity, to yield the CSFRB scheme. Additionally, this scheme is divided into offline computation and online selection, where main work will be finished in former one so as to decrease the complexity further. Finally, extensive simulation results illustrate the significant performance improvement of the proposed CSFRB scheme compared to the existing one in different scenarios.

In this paper, a cluster-based virtual multiple-input multiple-output (MIMO) transmission architecture is proposed for energy-constrained wireless sensor networks. In the proposed architecture, instead of using cluster members as cooperative nodes, multiple cluster heads cooperate to form virtual antenna array so that MIMO transmission can be implemented. According to the MIMO techniques used in this architecture, two different schemes, vertical Bell Laboratories layered space-time (V-BLAST) based cluster heads cooperative transmission (VCHCT) and space time block code (STBC) based cluster heads cooperative transmission (SCHCT), are developed. Based on the communication energy consumption model, the overall energy consumption model for both VCHCT and SCHCT are derived. Detailed comparison between these two schemes and the original low-energy adaptive clustering hierarchy (LEACH) is performed to investigate the performance of these two schemes. Simulation results not only verify the theoretical analysis but also show that the two schemes have their specific application scenarios. When the sink is far from the sensor area, SCHCT scheme is much more energy efficient than LEACH and VCHCT scheme even if it consumes additional inter-cluster communication energy. When the distance to sink is near the sensor area, VCHCT is preferable.

In cooperative spectrum sensing, more secondary user makes more opportunity for detecting the vacant spectrums, which resulting the spectrum utilization improved, however much bandwidth would be occupied for sending the local observation results, inducing the reduced secondary throughput. In this paper, an adaptive algorithm for selecting detection threshold was proposed, where the maximized secondary throughput can always be achieved while assuring sufficient protection to primary user, regardless of the number of sensing users in cognitive radio networks. Theoretical analysis and simulation results validate the proposed scheme.

In this paper, we consider the joint relay selection and power allocation problem for two-way relay systems with multiple relay nodes. Traditionally, relay selection schemes are primarily focused on selecting one relay node to maximize the transmission sum rate or minimize the outage probability. If so, it is possible to cause certain relay nodes overloaded. In addition, the joint relay selection and power allocation problem is a mixed integer program problem and prohibitive in terms of complexity. Therefore, we propose a novel low complexity joint relay selection and power allocation algorithm with proportional fair scheduling to get the load-balancing among potential relays. Simulation results turn out that, compared with round-robin schemes and max sum rate schemes, the proposed algorithm can achieve the tradeoff between system transmission sum rate and load-balancing.

With the development of wireless networks, the amount of multiple services increased sharply in recent years. High quality multiple services with low price are urgently needed especially in new generation mobile communication systems，e.g., 3G/LTE networks. It is important to enhance the availability of data service resources. Services have strong association which are used by clients with similar behavior habits in networks. Such feature results in service behavior convergence (SBC) and its utilization will enhance resource efficiency. This paper proposes two applications of service behavior: service prediction and a scheduling algorithm which enhances bandwidth efficiency. Convergence cells are classified according to SBC and hot-spot services are broadcasted separately in each convergence cell. It is demonstrated by stimulation that the bandwidth is saved 80% more than classical cellular system and nearly 20 % more than traditional broadcasting system.

Orthogonal frequency division multiplexing (OFDM) is considered to be one of the promising schemes for cognitive radios (CR) systems, due to its flexibility in spectrum shaping. However, the traditional way of spectrum-notching failed to suppress out-of-band leakage enough, resulting in interference with licensed users (LUs). A novel spectrum shaping scheme is proposed in this article, where a precoder with interference suppression sequence (ISS) is for the first time introduced for shaping the spectrum of OFDM signals in OFDM-based CR systems. The precoder matrix together with ISS matrix is obtained by minimizing the power of out-of-band interference, which results in the sufficient interference suppression of OFDM signal to LUs. Analysis and simulation results show that the proposed scheme can significantly suppress the interference power to LUs at a little cost of precoding efficiency. Meanwhile, the peak-to-average-power-ratio (PAPR) is invariable and the bit-error-rate (BER) performance over Rayleigh fading channel is improved.

Cooperative diversity is one of the most effective ways to mitigate the fading effect of wireless channels and obtain the spatial gain in wireless networks. In this paper, an optimal power allocation (OPA) scheme for a cooperative communication system using the amplify-and-forward (AF) transmit strategy with multiple relay users is proposed by minimizing the bit-error-rate (BER) at the destination under the constraint of the total transmit power of both the source user and the relay users. Simulation results indicate that the proposed power allocation method can achieve significant BER performance improvement than using the equal power allocation (EPA) scheme，while still attains low complexity. The system performance is improved significantly with the increasing of the number of relay users at high signal-noise ratio (SNR). However, at low SNR, the system performance decreases when the relay number increases. Thus, an adaptive relay selection scheme may be used to choose the appropriate relay numbers in different transmission scenarios to provide system performance improvement and keep the power allocation scheme with low complexity.

In multiple-input multiple-output (MIMO) systems, space–time block codes (STBCs) from orthogonal designs (ODs) and coordinate interleaved orthogonal designs (CIOD) have been attracting wider attention due to their amenability for fast (single symbol) maximum-likelihood (ML) decoding, and full-rate with full-rank over quasi-static fading channels. However, most of these codes, for transmitting antennas more than 4, have large number of zero entries in their codeword matrix. Due to the zero entries in the design, the transmitting antennas need to be switched on and off imposing severe hardware constraints. To solve this problem, we propose a method to generate a new class of no-zero-entry single symbol maximum likelihood decodable STBCs (NZESSDCs), which is based on coordinate interleaving and group precoding technique. The ability of the proposed group precoding based NZESSDCs (called G-NZESSDCs) on single symbol ML Decoding and full diversity are analyzed and derived. The performance evaluation is accomplished by numerical simulation and is compared with recently reported NZESSDCs (called C-NZESSDCs). Compared with C-NZESSDCs, the proposed G-NZESSDCs have same bit-error-rate (BER) performance and better peak-to-average ratio (PAPR) performance.

Differential evolution (DE) algorithm has attracted more and more attention due to its fast optimization performance and good stability. When DE algorithm is applied into multi-constrained multicast routing optimization problem, a common solution to such problem is to merge the paths into a tree after finding paths from the source node to each destination node. This method maybe obtains the better result, but it can consume a lot of computational time. To solve the problem, a tree-based DE algorithm is introduced in this paper. The central operations of the algorithm are realized with tree structure. This method saves the time of finding paths and integrating them to construct a multicast tree. The experiments show that the proposed algorithm can achieve higher success rate than several common algorithms with much smaller running time for different networks.

Modified largest weighted delay first (M-LWDF) is a typical packet scheduling algorithm for supporting hybrid real-time services over wireless networks. However, so far, there is little literature available regarding the theoretic analysis of M-LWDF fairness. This paper gives a theoretic analysis of M-LWDF fairness, which shows that M-LWDF fairness is related to channel condition, packet’s arrival process and the ratio of quality of service (QoS) requirements of different service queues. Given service QoS requirements and other parameters related to channel model and packet’s arrival process, the fairness is merely related to the ratio of the number of users in the service queues. Based on the analysis, an enhanced M-LWDF algorithm (EM-LWDF) is proposed and demonstrated in this paper. EM-LWDF is strictly designed in light of the fairness criteria of QoS requirements, so its fairness is almost not related to the ratio of the number of users in the service queues, and the theoretical value of fairness index is equal to 1. Simulation results validate the theoretic analysis and show the effectiveness of EM-LWDF in improving fairness.

Independent quality of service (QoS) registration center is difficult to monitor QoS with lots of requests in Internet environment with a large number of services and lots of service requests. It is able to reduce the load and decrease the failure rate by using multiple QoS registration centers to monitor QoS of some services with lots of requests. In addition, the heterogeneous QoS data close to user’s habitual expression and adapts to the environment with complexity and uncertainty. This paper introduces a novel Web service composition algorithm based on technique for order preference by similarity to an ideal solution (TOPSIS) (WSCA_TOPSIS) to solve the above difficulties for the first time. WSCA_TOPSIS can support multiple decision-makers and heterogeneous QoS data. It includes three main steps: normalizing decision matrix, evaluating alternatives synthetically and evaluating group alternatives synthetically. Other contributions of the paper include a novel algorithm of aggregating QoS and a set of experiments that demonstrate the benefits and effectiveness of our approach. Experimental results show that the proposed algorithm can better support Web service composition with heterogeneous QoS data and multiple decision-makers.

Network selection is crucial in improving the performance of heterogeneous wireless access systems. Most of previous work on network selection or radio resource allocation concentrates on the capability of each available network and ignores the time-varying nature of wireless media due to channel fading. However, the channel condition determines the state of each wireless network and plays a vital role in ensuring quality of service in multi-radio access environment. In this article, we propose a network selection policy using stochastic control theory considering the time-varying and stochastic character of wireless channels. The proposed scheme selects one network among different alternatives in each decision epoch according to the channel state of each network, which is modeled as finite-state Markov channel, with the objectives of increasing the data-rate, decreasing the bit error rate and minishing the delay. The procedure of network selection is formulated as a stochastic control problem, which can be solved using linear programming and primal-dual index heuristic algorithm. Simulation results are presented to show that network selection has great impact on the system performance, and the proposed scheme can improve the performance significantly.

The Internet today originates from the advanced research project agency network (ARPANET) and evolves constantly during the past years. However, with incremental ‘patches’ on the Internet, the current network architecture faces many problems which are too difficult to solve. In the light of recent interest in re-designing the Internet, the separation of core network and customer edge network, and the separation of identifier and locator receive wide consensus among scientists. We follow this direction and propose a new hierarchical network with diversified customer edge access (HNDCE) in this paper. We use switching addresses, routing addresses and identifiers to implement a true core/edge and locator/identifier split. In the core network, hierarchical switching addresses combined with tree topology makes routing replaced by switching. The Viliant load-balancing (VLB) structure is used here to compensate the topology’s reliability and scalability. In the customer edge network, the split of locator and identifier makes it possible to deploy various routing schemes and new services. Hierarchical mapping system is also designed to support this new architecture.

A cross-layer optimized query routing mismatch alleviation (QRMA) architecture is proposed to mitigate the problem of query routing mismatch (QRM) phenomenon between the structured peer to peer (P2P) overlay and the routing layer in mobile Ad-hoc networks (MANETs), which is an important issue that results in the inefficiency of lookup process in the system. Explicated with the representative Chord protocol, the proposal exploits the information of topologic neighbors in the routing layer of MANETs to find if there is any optimized alternative next hop in P2P overlay during conventional lookup progress. Once an alternative next hop is detected, it will take the shortcut to accelerate the query procedure and therefore alleviate the QRM problem in scalable MANETs without any assistance of affiliation equipments such as GPS device. The probability of finding out such an alternative node is formulated and the factors that could increase the chance are discussed. The simulation results show that the proposed architecture can effectively alleviate the QRM problem and significantly improve the system performance compared with the conventional mechanism.

In this paper, we present the design of an integrated low noise amplifier (LNA) for wireless local area network (WLAN) applications in the 5.15–5.825 GHz range using a SiGe BiCMOS technology. A novel method that can determine both the optimum bias point and the frequency point for achieving the minimum noise figure is put forward. The method can be used to determine the optimum impedance over a relevant wider operating frequency range. The results show that this kind of optimizing method is more suitable for the WLAN circuits design. The LNA gain is optimized and the noise figure (NF) is reduced. This method can also achieve the noise match and power match simultaneously. This proposal is applied on designing a LNA for IEEE 802.11a WLAN. The LNA exhibits a power gain large than 16 dB from 5.15 to 5.825 GHz range. The noise figure is lower than 2 dB. The OIP3 is 8 dBm. Also the LNA is matched to 50 Ω input impedance with 6 mA DC current for differential design.

Four kinds of sequences generated by single cycle triangular function (T-function) are investigated to check the possibility for a single cycle T-function to be a cryptographic component in stream ciphers. Based on the special properties of single cycle T-function and an algorithm due to Wei, linear complexities of these four kinds of sequence are all acquired. The results show that single cycle T-function sequences have high linear complexity. Therefore, T-function satisfies the essential requirements being a basic component of stream cipher.