Abstract : Worldwide regulations for short range communication devices allow the unlicensed use of several Gigahertz of bandwidth in the frequency band around 60 GHz. This 60GHz band is ideally suited for applications like very high data rate, energy-autonomous wireless sensor networks or Gbit/s multimedia links with low power constraints. Not long ago, radio interfaces that operate in the millimeter-wave frequency range could only be realized using expensive compound semiconductor technologies. Today, the latest sub-micron CMOS technologies can be used to design 60GHz radio frequency integrated circuits (RFICs) at very low cost in mass production. This thesis is part of an effort to realize a low power System in Package (SiP) including both the radio interface (with baseband and RF circuitry) and an antenna array to directly transmit and receive a 60GHz signal. The first part of this thesis deals with the design of the low power RF transceiver front-end for the radio interface. The key building blocks of this RF front-end (amplifiers, mixers and a voltage controlled oscillator (VCO)) are designed, realized and measured using the 65nm CMOS technology of ST Microelectronics. Full custom active and passive devices are developed and characterized for the use within these building blocks. An important step towards the full integration of the RF transceiver front-end is the assembly of these building blocks to form a basic receiver chip. Circuits with small chip size and low power consumption compared to the state of the art have been accomplished. The second part of this thesis concerns the development of behavioral models for the designed building blocks. These system level models are necessary to simulate the behavior of the entire SiP, which becomes too complex when using detailed circuit level models. In particular, a novel technique to model the transient, steady state and phase noise behavior of the VCO in the hardware description language VHDL-AMS is proposed and implemente d. The model uses a state space description to describe the dynamic behavior of the VCO. Its nonlinearity is approximated by artificial neural networks. A drastic reduction of simulation time with respect to the circuit level model has been achieved, while at the same time maintaining a very high level of accuracy.