@conference {19297,
	title = {FPGA-based design and implementation of the 3GPP-LTE physical layer using parameterized synchronous dataflow techniques},
	booktitle = {2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)},
	year = {2010},
	month = {2010},
	pages = {1510 - 1513},
	abstract = {Synchronous dataflow (SDF) is an ubiquitous dataflow model of computation that has been studied extensively for efficient simulation and software synthesis of DSP applications. In recent years, parameterized SDF (PSDF) has evolved as a useful framework for modeling SDF graphs in which arbitrary parameters can be changed dynamically. However, the potential to enable efficient hardware synthesis has been treated relatively sparsely in the literature for SDF and even more so for the newer, more general PSDF model. This paper investigates efficient FPGA-based design and implementation of the physical layer for 3GPP-Long Term Evolution (LTE), a next generation cellular standard. To capture the SDF behavior of the functional core of LTE along with higher level dynamics in the standard, we use a novel PSDF-based FPGA architecture framework. We implement our PSDF-based, LTE design framework using National Instrument{\textquoteright}s LabVIEW FPGA, a recently-introduced commercial platform for reconfigurable hardware implementation. We show that our framework can effectively model the dynamics of the LTE protocol, while also providing a synthesis framework for efficient FPGA implementation.},
	keywords = {3G mobile communication, 3GPP-long term evolution, 3GPP-LTE physical layer, 4G communication systems, Computational modeling, data flow analysis, data flow graphs, Dataflow modeling, Digital signal processing, DSP applications, Field programmable gate arrays, FPGA architecture framework, FPGA implementation, FPGA-based design, Hardware, hardware synthesis, Instruments, LabVIEW FPGA, Logic Design, LTE, next generation cellular standard, parameterized synchronous data flow technique, Pervasive computing, Physical layer, Physics computing, Production, PSDF graph, reconfigurable hardware implementation, Runtime, software synthesis, Ubiquitous Computing, ubiquitous data flow model},
	author = {Kee, Hojin and Bhattacharyya, Shuvra S. and Wong, I. and Yong Rao}
}
@conference {12086,
	title = {Achieving packet-level quality of service through scheduling in multirate WLANs},
	booktitle = {Vehicular Technology Conference, 2004. VTC2004-Fall. 2004 IEEE 60th},
	volume = {4},
	year = {2004},
	month = {2004/09/26/29},
	pages = {2730- 2734 Vol. 4 - 2730- 2734 Vol. 4},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Wireless packet scheduling has been a popular paradigm to achieve packet-level QoS in terms of fairness and throughput in the presence of channel errors. However, the current design does not anticipate the multi-rate capability offered by the IEEE 802.11a/b/g physical layer, thus suffering significant performance degradation in 802.11 WLANs. In this paper, we propose multirate wireless fair scheduling (WMFS). In MWFS, each flow is granted a temporal fair share of the channel, in contrast to the throughput fair share adopted by existing algorithms. Therefore, each flow receives services in proportion to its perceived transmission rate, and high-rate flows are able to opportunistically exploit their good channel conditions and receive more services. MWFS also renovates the compensation model in order to allow for error-prone flows to catch up, thus ensuring fairness for all flows over error-prone channels. We demonstrate the effectiveness of MWFS through both simulations and analysis. Especially, WMFS achieves system throughput 159\% of state-of-the-art scheduling algorithms in simulated scenarios.},
	keywords = {Analytical models, channel conditions, channel errors, channel temporal fair share, compensation, Computer science, Delay, error-prone flow compensation, IEEE 802.11a/b/g physical layer, multirate wireless fair scheduling, multirate WLAN, packet radio networks, packet-level quality of service, Physical layer, Processor scheduling, QoS, quality of service, radio access networks, Scheduling algorithm, Throughput, throughput fairness, USA Councils, Wireless LAN, wireless packet scheduling, WMFS},
	isbn = {0-7803-8521-7},
	doi = {10.1109/VETECF.2004.1400554},
	author = {Yuan Yuan and Daqing Gu and Arbaugh, William A. and Jinyun Zhang}
}
@conference {12100,
	title = {High-performance MAC for high-capacity wireless LANs},
	booktitle = {13th International Conference on Computer Communications and Networks, 2004. ICCCN 2004. Proceedings},
	year = {2004},
	month = {2004/10/11/13},
	pages = {167 - 172},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The next-generation wireless technologies, e.g., 802.11n and 802.15.3a, offer a physical-layer speed at least an-order-of-magnitude higher than the current standards. However, direct application of current MACs leads to high protocol overhead and significant throughput degradation. In this paper, we propose ADCA, a high-performance MAC that works with high-capacity physical layer. ADCA exploits two ideas of adaptive batch transmission and opportunistic selection of high-rate hosts to simultaneously reduce the overhead and improve the aggregate throughput. It opportunistically favors high-rate hosts by providing higher access probability and more access time, while ensuring each low-rate host certain minimum amount of channel access time. Simulations show that the ADCA design increases the throughput by 112\% and reduces the average delay by 55\% compared with the legacy DCF. It delivers more than 100 Mbps MAC-layer throughput as compared with 35 Mbps offered by the legacy MAC},
	keywords = {35 Mbit/s, access protocols, Aggregates, Bandwidth, batch transmission, Computer science, Educational institutions, high-capacity wireless LAN, high-performance MAC, Laboratories, Local area networks, Media Access Protocol, opportunistic selection, Physical layer, probability, Throughput, Wireless LAN},
	isbn = {0-7803-8814-3},
	doi = {10.1109/ICCCN.2004.1401615},
	author = {Yuan Yuan and Daqing Gu and Arbaugh, William A. and Jinyun Zhang}
}
