In this paper, we present a LUT-based efficient impulse shaping for direct synthesis of digital communication signal at arbitrary symbol rate. Compared with general approaches where sampling clock changes according to the symbol rate thus signal quality degrade as result of a complex analog hardware structure, or involving a fractional interpolation which consumes considerable computational resource, this new approach allows FPGA to synthesis variable high data rata signal with high quality directly at a fixed sampling rate which simplify the hardware structure and saves computational resource consumption. With some little modifications, the presented scheme could be easily adapted to 8PSK, 16QAM and other arbitrary amplitude-phase-modulation constellations. A hardware prototype has been built to verify the presented algorithms. In particular, we have achieved 4.8 Gsps parallel impulse shaping which supports input symbol rate ranging from 100 Ksps to 600 Msps.

We have previously proposed and implemented a small form factor and low cost 100G optical transmission system using inverse-multiplexing technology and MLD (Multiplex-Lane Distribution) mechanism [1]. Based on this 100G system, we will further implement a transmission and network management system for multiple 100G application via stacking technology. This technology can incrementally realize the standard 100G OTN or 100G Ethernet capacity expansion with a centralized network element management at one node. The stacking system contains both network management port stacking and optical wavelength stacking. Our test results show that we can stack at least four devices with stable performance, which means a maximum transmission capacity of 400G, but with one IP address or one NE (network element) network management. This technology has a significant advantage comparing with a large rack equipment in term of device cost and flexible 100G bandwidth addition, as well as simple management function.

Vehicle-to-vehicle (V2V) communication has been widely considered as a promising approach for delivering messages between vehicles. However, the highly dynamic topology caused by vehicle mobility makes V2V communication unreliable, especially in the case where the SINR at the receiver below a given threshold. To address the problem, we propose a resource allocation scheme for transmission non-safety messages in cellular vehicular networks. In this scheme, the instability of vehicular network topology has been taken into account. Furthermore, to make the SINR at the receiver under given constraints, distance prediction as well as extra resource allocation is adopted in the design of the scheme. Simulation results demonstrate that the proposed scheme greatly improves the wireless resource utilization.

In manned/unmanned-aerial-vehicles team, the situation awareness level of manned-aerial-vehicle (MAV) pilot affects the pilot’s cognitive state. Evaluating the pilot’s situation awareness level will enhance the cognitive and interactive capabilities of unmanned-aerial-vehicle (UAV) and MAV. This paper proposes an assessment method of pilot’s situation awareness, which is based on attention resource allocation theory and conditional probability cognitive process. Using the presented method, the situation awareness level of pilot could be quantified and evaluated reasonably. Finally the paper simulated the model at different levels of autonomy (LOA) to demonstrate the rationality of the model.

For the further performance improvement of Cognitive Radio systems, providing accurate or comprehensive information support to Cognitive Radio devices or networks, there is a use of “Radio Environment Map (REM)”, which presents multi-dimensional information of radio environments and scenarios. With the study of Spatial Interpolation, a method of constructing REM is proposed, and the performance of each algorithm is compared. Experiments show that the RMSM algorithm has advantages like high efficiency and low error, which can be used for the construction of REM.

As a huge numbers of heterogeneous devices will be connected in social cognitive radio networks (SCRNs), it needs more frequency spectrum. Moreover, dynamic spectrum availability and heterogeneous devices make it more difficult for routing design in SCRNs. Opportunistic routing (OR) can leverage the broadcast nature of wireless channels, and then can enhance network performance. In this work, we propose an energy aware coded OR (ECOR) in SCRNs, which jointly considers energy efficiency and social feature for designing coded OR. In the proposed OR, we exploit a new scheme for candidate selection and use network coding in data transmission between selected nodes in SCRNs. In addition, we propose a game-theoretic approach to decide forwarding candidate set which is based on auction mechanism. The simulation results demonstrate that the ECOR performs better compared with existing routing in SCRNs in terms of hop count and packet delivery ratio.

This paper presents a novel energy-efficient MAC Protocol designed for Body Sensor networks (BSN) focusing towards pervasive healthcare applications. BSN nodes are usually attached to the human body to track vital health signs such as body temperature, activity or heart-rate. Unlike traditional wireless sensor networks, the nodes in BSN are not deployed in an adhoc manner. The network connectivity is usually centrally managed and all communications are single-hop. The BSN has to be dependable in order to ensure the availability and reliability of the data received. Hence, it is necessary to reduce energy consumption in order to prolong the operation of the network without frequent outage. It is common to duty cycle the sensor nodes to preserve the battery utilization. However, the communication between the sensing node and receiving node can be interfered by human movement that can lead to energy wastage. In this paper, A Multi-Modal Opportunistic Transmission with Energy Saving (M-MOTES) is proposed. M-MOTES uses the opportunistic transmission approach and the human kinematics to duty-cycling the node. Extensive experiments performed on real hardware show that M-MOTES can reduce the battery power consumption without affecting the packet reliability.

To support QoS of time-sensitive services in Ethernet, IEEE has proposed a set of standards for transporting and forwarding real-time content over Ethernet known as Audio Video Bridging (AVB) with bandwidth reservation and priority isolation. AVB traffic is granted highest priority to ensure its transmission while low-priority traffic follows Strict Priority (SP). However, due to restrictions of SP algorithm, low-priority traffic may suffer a problem of starvation. To solve the problem, we propose a BP neural network based self-tuning controller (BPSC) over a probability selector to manage the transmission of best effort (BE) traffic in AVB switched Ethernet. This paper introduces the model of BPSC, followed by an simulation to demonstrate that BPSC could operate effectively and dynamically. The result shows that BPSC not only has the ability to manage the transmission precisely, but also shows both effectiveness and robustness.

With the explosive growth of vehicles, current vehicular networks, based on CSMA/CA, are unable to guarantee the low latency and high reliability for safety message transmission under heavy traffic condition. In this paper, we propose a Priority-based Multi-carrier Random Access with Carrier Switching (PMRA/CS) scheme, which is designed for OFDMA-based vehicular networks to support massive concurrent access of large number of vehicles. Compared to CSMA/CA, PMRA/CS utilizes a special short detecting frame to resolve the alarm message collision with less cost. Moreover, the scheme provides more opportunities for vehicles to access the channel in one period by allowing the loser of one sub-carrier to switch to another idle one and continue to access contention. Use of vehicle priority assignment makes the proposed strategy more applicable to realistic scenarios. Furthermore, we provide some theoretical analysis of the proposed scheme combined with derived formula derivation. Simulation results are provided to demonstrate the improvements of message sending success rate and average delay reduction of our proposed scheme.

In the work, we design a novel EE-eICIC algorithm to deal with determining the amount of almost blank subframes (ABS) and user should associate with pico or macro from energy efficiency perspective. Using a generalized fractional programming theory and the convex programming, we propose an iterative and relaxed-rounding algorithm to deal with the problem. Numerical experiments show that the proposed EE-eICIC method can obtain superior performance comparing with state-of-the-art algorithms in terms of energy efficiency of system.