Manfred Zimmermann

Object oriented signal data structures in VLSI implementations of wireless modems

In real-world very large scale integration (VLSI) silicon implementations of 3GPP wireless modems modularity of system on chip (SoC) architecture and efficiency in terms of power and die size are crucial criteria. This is particularly true for the signal processing subsystem as the data flow volume in the modems physical layer is proportionally high. One architectural method to deal with modularity and power efficiency is to focus on well defined communication structures inbetween the dedicated signal processing units and well formatted data objects stored locally in intermediate buffers to keep data transport effort low. Contrary to that, die size reduction often implies the usage of centralized and shared entities like memories and busses. This paper presents an example for data communication structure and data format of the radio frame buffers in a UMTS/HSDPA/MBMS wireless modem receive path and how an object oriented system design approach combines those optimization strategies according to the initially mentioned criteria.

Symbol Data Organization in a WB-CDMA Modem

For a System-on-Chip (SoC) implementation of mass market devices like a wireless modem user equipment it is crucial -in addition to fulfilling the standardized functional requirements -to optimize both silicon die size and power dissipation. In current VLSI technologies at 65 nm and beneath, beside an optimized logic implementation, a careful dimensioning of all memories is a must. This applies especially to those synchronous random access memories (SRAM) which have to be built on-die because the data throughput is inevitable high like in the signal processing part of a modems physical layer. This paper presents as an example for the receive path of a WB-CDMA modem a solution for a low power data organization of the frame-wise buffered symbol-streams in between demodulators and channel decoder. This solution is self-adapting in real time to the permanent changing data rates and volume respectively.