Performance Analysis of TETRA and TAPS and Implications for Future Broadband Public Safety Communication Systems

This paper discusses the traffic performance of TETRA, TAPS, and a new approach for broadband ad hoc communication systems. The results show the performance of TETRA and TAPS regarding multimedia applications for public safety forces and what will be possible with selforganizing broadband networks. The results were obtained with three simulation tools developed at the chair. The TETRA simulator TETRIS implements the protocols of the TETRA air interface, a channel model and load generators for data and voice applications, and provides simulation results for Quality of Service (QoS) measures like random access delay or transmission delay, see Section 1. Because TAPS is an adaptation of (E)GPRS for TETRA, our GPRS simulator was used. Simulation results for quality of service measures of TAPS for the different applications and GPRS system measures are based on the simulation tool GPRSim that models the application and user behavior, the TCP/IP and WAP protocol architecture, the GPRS protocol architecture and the radio channel, see Section 2. Finally, design issues of self-organizing broadband wireless networks are examined in Section 3. As central-ized solutions suffer from many inherent disadvantages, the responsibilities of organizing and controlling of self-organizing networks should be fully distributed among wireless stations themselves. Wireless CHannel ori-ented Ad-Hoc Multihop Broadband (W-CHAMB) ideas that meet QoS demands for high performance services and realize statistical multiplexing of bursty traffic in a fully distributed and efficient manner are described in detail. The superiority of the performance of the W-CHAMB network can be seen in comparison with that of packet-oriented IEEE 802.11 WLAN. The hidden station problem is completely resolved by means of the energy signal (E-signal) solution. The performance gain of E-signal solution over the RTS/CTS mechanism is evaluated through computer simulation. Finally, the effect of network connectivity on the traffic performance is discussed.