This paper presents a low-power LDPC decoder that can be used in Multimedia Wireless Sensor Networks. Three low power design techniques are proposed in the decoder design: a layered decoding algorithm, a modified Benes network and a modified memory bypassing scheme. The proposed decoder is implemented in TSMC 0.13 µm, 1.2 V CMOS process. Experiments show that when the clock frequency is 32 MHz, the power consumption of the proposed decoder is 38.4 mW, the energy efficiency is 53.3 pJ/bit/ite and the core area is 1.8 mm2.

A wide range, low jitter Duty Cycle Corrector (DCC) based on continuous-time integrator is proposed. It introduces little added jitter in the sampling edge, which make it good candidate for pipelined ADC application. The circuit is implemented in CMOS 0.35 µm 2P4M Mixed Signal process. The experimental results show the circuit can work for a wide frequency range from 500 kHz to 280 MHz, with a correction error within 50%1% under 200 MHz, and the acceptable duty cycle can be as wide as 1-99% for low frequency inputs.

A 1.8 V, 5 GHz low power frequency synthesizer for Wireless Sensor Networks is presented in 0.18 µm CMOS technology. A low power phase-switching prescaler is designed, and the current mode phase rotator is merged into the first divide-by-2 circuit of the prescaler to reduce power and propagation delay. An improved charge pump circuit is proposed to compensate for the dynamic effects with the charge pump. By a divide-by-2 circuit, the frequency synthesizer can provide a 2.324-2.714 GHz quadrature output frequency in 1 MHz steps with a 4 MHz reference frequency. The measured output phase noise is -110 dBc/Hz at 1-MHz offset frequency. The power consumption of the PLL is 11.2 mW at 1.8 V supply voltage.

Power-aware scheduling of periodic tasks in real-time systems has been extensively studied to save energy while still meeting the performance requirement. Many previous studies use the probability information of tasks' execution cycles to assist the scheduling. However, most of these approaches adopt heuristic algorithms to cope with realistic CPU models with discrete frequencies and cannot achieve the globally optimal solution. Sometimes they even show worse results than non-stochastic DVS schemes. This paper presents an optimal DVS scheme for frame-based real-time systems under realistic power models in which the processor provides only a limited number of speeds and no assumption is made on power/frequency relation. A suboptimal DVS scheme is also presented in this paper to work out a solution near enough to the optimal one with only polynomial time expense. Experiment results show that the proposed algorithm can save at most 40% more energy compared with previous ones.

In this paper, a modified Belief Propagation (BP) decoding algorithm for low-density parity check (LDPC) codes based on minimum mean square error (MMSE) criterion is proposed. This modified algorithm uses linear equation to replace the hyperbolic function in the original BP algorithm and optimizes the linear approximation error based on MMSE criterion. As a result, compared with the standard BP algorithm the computational complexity is reduced significantly as the modified algorithm requires only addition operations to implement. Besides that simulation results show our modified algorithm can achieve an error performance very close to the BP algorithm on the additive white Gaussian noise channel.