Reconfiguration for Sensitivity Technique (RST) is presented as an approach for maintaining QoS in stream-based applications running on embedded systems. It is a co-design approach that uses the reconfiguration and sensitivity metrics for QoS awareness; the former for run-time reconfiguration in response to stimuli from the latter. The effectiveness of RST was tested after we used our CHARMS algorithm to screen out 95.17% of the mapping-cases for a H.263 encoder. Our tests showed a 99.25% QoS provisioning-up-time-level at any given instant, based on available battery power, using RST as compared to 80.62% with Performance Aware Reconfiguration of Software Systems(PARSY), 58.83% with Reconfigurable Service Composition(RSC) and 41.67% without RST.
OFDM system divides a wideband transmission bandwidth into several overlapped narrowband subcarriers to avoid the serious frequency selective fading problem. However, if Timing Offset (TO) and Carrier Frequency Offset (CFO) exist between the Transmitter (Tx) and Receiver (Rx), OFDM system will suffer the Inter-Symbol Interference (ISI) and Inter-Carrier Interference (ICI) that degrade the system performance dramatically. In this paper, we propose a simple modification of the S&C method. We adopt the overlap concept to reduce the plateau problem. Simulation results show that with this simple modification, it can improve the timing synchronization performance of the S&C method greatly.
This paper considers a static downlink power allocation algorithm for a multi-cell system in order to maximize the average system throughput. Based on observation that at least one base station (BS) has to transmit at the maximum power for optimal power allocation, and the optimal binary power allocation (OBPA) may still cause excessive interference, we propose a multi-stage greedy power allocation (MSGPA) which allows some of BSs to have several discrete transmit power levels by introducing multi-stage power adjustment. The simulation results show that the MSGPA outperforms the OBPA while significantly reducing complexity and transmit power as well.
A novel design of monolithic RF-MEMS (radio frequency micro electro mechanical systems) phase shifter for Ku-band has been successfully developed based on a mechanically movable switched-line waveguide. The structures of MEMS actuators, switch contacts, and MEMS coplanar waveguides have been optimized in terms of insertion loss by utilizing the both sides of an SOI (silicon on insulator) wafer and by using the SOI layer-separation technique, where microwave waveguides and actuators are allocated on the handle wafer and the active layer of SOI, respectively. RF performance was measured on a developed 1-bit MEMS phase shifter, and we obtained insertion loss of -1.64 to -1.82dB/bit, return loss of -8.92 to -12.60dB/bit, and isolation of -40.29dB/bit at 12.5GHz. Phase-error for the 22.5-degree phase shifter was found to be 5.5degree/bit at 12.5GHz.
An optoelectronic CMOS memory technology is proposed where photon induced floating body effect stimulates switching and hysteresis in the transistor. The floating body effect is induced by exceedingly few carriers generated by two photon absorption. In this paper we present the structure of proposing device and numerically validated the device by Atlas device simulator from SILVACO Corporation.
Since modern MCM (Multi Chip Module) is required to provide higher performance, MCM's density and power consumption has been increased very rapidly. Increase of chip density and power consumption lead to hot spots which accelerate the device's life time and result in device failure in the long run. In this paper, a new placement method is presented to improve the MCM's reliability using a TPSA (Two-Phase Simulated Annealing) algorithm. The TPSA searches the lowest failure rate placement of MCM perturbing higher failure rate phase and lower failure rate phase at the same time to generate a new movement. The proposed algorithm is applied to the IBM (International Business Machines) MCM device for searching an optimal solution and for comparing optimized results with other optimization results. The result shows improvement in reliability and temperature distribution satisfying constraints.