Information Outlook, August 2005

Volume 9, Issue 8https://scholarworks.sjsu.edu/sla_io_2005/1007/thumbnail.jp

IEEE Access special section editorial: Mission critical public-safety communications: architectures, enabling technologies, and future applications

Disaster management organizations such as fire brigades, rescue teams, and emergency medical service providers have a high priority demand to communicate with each other and with the victims by using mission-critical voice and data communications [item 1) in the Appendix]. In recent years, public safety agencies and organizations have started planning to evolve their existing land mobile radio system (LMRS) with long-term evolution (LTE)-based public safety solutions which provides broadband, ubiquitous, and mission-critical voice and data services. LTE provides high bandwidth and low latency services to the customers using internet protocol-based LTE network. Since mission critical communication services have different demands and priorities for dynamically varying situations for disaster-hit areas, the architecture and the communication technologies of the existing LTE networks need to be upgraded with a system that has the capability to respond efficiently and in a timely manner during critical situations

A joint-channel diagonalization for multiuser MIMO antenna systems

In this paper, we address the problem of improving the performance of multiuser space-division multiplexing (SDM) systems where multiple independent signal streams can be transmitted in the same frequency and time slot. The problem is important in multiuser multiple-input multiple-output systems where communication from one base station to many mobile stations can occur simultaneously. Our objective is to devise a multiuser linear space-time precoder for simultaneous channel diagonalization of the multiuser channels enabling SDM. Our new approach is based on diagonalizing the multiuser channel matrices and we use a variation of successive Jacobi rotations. In addition to the diagonalization, our approach attempts to optimize the resultant channel gains for performance enhancement. Our method is valid for both frequency-flat and frequency-selective fading channels but we assume that the base station knows all the channels and that they are quasi-stationary

Spartan Daily, March 21, 1991

Volume 96, Issue 37https://scholarworks.sjsu.edu/spartandaily/8105/thumbnail.jp

Focal Spot, Fall 1982

https://digitalcommons.wustl.edu/focal_spot_archives/1032/thumbnail.jp

Special Libraries, Summer 1992

Volume 83, Issue 3https://scholarworks.sjsu.edu/sla_sl_1992/1002/thumbnail.jp

Information Outlook, May 2007

Volume 11, Issue 5https://scholarworks.sjsu.edu/sla_io_2007/1004/thumbnail.jp

Power versus Bandwidth Efficiency in Wireless Communications: from Economic Sustainability to Green Radio

The continuous investment in research and development, aimed at improving the utility and the efficiency of wireless communications networks, brings about a wealth of theoretical knowledge and practical engineering solutions. Remarkably. however,a widely accepted choice of a criterion characterizing the overall efficiency of a wireless network remains an open problem

A connection-level call admission control using genetic algorithm for MultiClass multimedia services in wireless networks

Call admission control in a wireless cell in a personal communication system (PCS) can be modeled as an M/M/C/C queuing system with m classes of users. Semi-Markov Decision Process (SMDP) can be used to optimize channel utilization with upper bounds on handoff blocking probabilities as Quality of Service constraints. However, this method is too time-consuming and therefore it fails when state space and action space are large. In this paper, we apply a genetic algorithm approach to address the situation when the SMDP approach fails. We code call admission control decisions as binary strings, where a value of “1” in the position i (i=1,…m) of a decision string stands for the decision of accepting a call in class-i; a value of “0” in the position i of the decision string stands for the decision of rejecting a call in class-i. The coded binary strings are feed into the genetic algorithm, and the resulting binary strings are founded to be near optimal call admission control decisions. Simulation results from the genetic algorithm are compared with the optimal solutions obtained from linear programming for the SMDP approach. The results reveal that the genetic algorithm approximates the optimal approach very well with less complexity