In wireless networks, sleep mode based power saving mechanisms can reduce the energy consumption at the expense of additional packet delay. This letter analyzes its packet queueing delay and wireless terminals' energy efficiency. Based on the analysis, optimal sleep window size can be derived to optimize terminal energy efficiency with delay constraint.

This paper presents a cascode-pair distributed amplifier design approach using 0.25 µm GaAs-based PHEMT MMIC technology, which covers 2-32 GHz. Electromagnetic simulation results show that this amplifier achieves 18 dB gain from 2 to 32 GHz and 0.5 dB gain flatness over the band. The reflected coefficients at the input and output ports are below -10 dB up to 27 GHz. The output power at 1 dB compression is greater than 24 dBm at 20 GHz. An appropriate feedback resistance can be utilized to improve P1 dB for about 6 dBm. The DOE (design of experiment) approach is carried out by a simulation tool for better performance and tolerance of the devices is also analyzed. The circuit configuration is capable of operating over ultra-broad band amplification.

The traffic load of cellular networks varies in both time and spatial domains, causing many base stations (BS) to be under-utilized. Assisted by cell zooming, dynamic BS sleep control is considered as an effective way to improve energy efficiency during low traffic hours. Therefore, how densely the BSs should be deployed with cell zooming and BS sleeping is an important issue. In this paper, we explore the energy-optimal cellular network planning problem with dynamic BS sleeping and cell zooming for the cases in which traffic is uniformly distributed in space but time-varying. To guarantee the quality of multi-class services, an approximation method based on Erlang formula is proposed. Extensive simulations under our predefined scenarios show that about half of energy consumption can be saved through dynamic BS sleeping and power control. Surprisingly, the energy-optimal BS density we obtained is larger than the one without considering BS sleeping. In other words, deploying more BSs may help to save energy if dynamic BS sleeping is executed.

This paper presents an analysis of electrically large antennas using the adaptive integral method (AIM). The arbitrarily shaped perfectly conducting surfaces are modeled using triangular patches and the associated electric field integral equation (EFIE) is solved for computing the radiation patterns of these antennas. The method of moments (MoM) is used to discretize the integral equations and the resultant matrix system will be solved by an iterative solver. The AIM is employed in the iterative solver to speed up the matrix-vector multiplication and to reduce the memory requirement. As specific applications, radiation patterns of parabolic reflectors and X-band horns are computed using the proposed method.