DCPECCS 2014 Abstracts

Full Papers
Paper Nr: 2

Scalable Algorithm Design for High-Level Synthesis and Optimization of Latency Insensitive Systems


Wei Tang and Forrest Brewer

Abstract: This research consists of two parts. The first part studies exploration of efficient and scalable high-level synthesis (HLS) algorithms for conventional synchronous designs. The second part explores optimization strategies for synchronous latency insensitive (LI) systems. Crucial to design quality and productivity, current HLS algorithms suffer a good balance between complexity and quality. Existing high-quality HLS algorithms have at least O(N^{3}) complexity. This research develops algorithms that can synthesize applications with sub-quadratic run time. Compared to the state-of-the-art HLS algorithms, ours can generate better or equal latency solutions. The proposed algorithms have the potential to release designers from using different abstraction levels for large scale designs. LI design paradigm, a correct-by-construction design paradigm, provides a fast way for design prototyping which is based on manual observation. This research proposes automatic optimization algorithms to even speed up the prototype process. Algorithm efficacy is tested on a practical micro-controller. Compared to carefully hand-crafted designs, our optimization algorithms can generate designs with better performance and less area usage.

Paper Nr: 3

Weighted Sum-rate Maximization for Multi-user Mimo-OFDM Downlink with ZF-DPC Methods


P. Krishna, T. Anil Kumar and K. Kishan Rao

Abstract: Multi -user MIMO techniques were born due to the urge of high data rates and spectral efficiency in 4G systems. For scenarios with a large number of users to be served in one cell, high capacity gains can be achieved by transmitting independent data streams to different users sharing the same time -frequency resources through the use of MIMO precoding. Linear precoding is employed in MU-MIMO communication system to improve the system capacity and to minimize the receiver complexity. The previous works on optimization algorithm to design a linear precoder to maximize the system capacity is assumed to have perfect channel state information (CSI) at the base station (BS).However the CSI available at the BS is imperfect due to channel estimation errors. With enough channel state information (CSI) at the transmitter, MIMO precoding allows to increase multi-user diversity gain. However, without a correct precoding vector selection, the interference between users can seriously degrade the overall network data rate. In a close-loop configuration, the base station (BS) receives from each user the preferred precoding vector and modulation and coding scheme (MCS).To achieve the highest multi -user diversity gains and avoid users interference, the BS needs to recalculate the precoding vector and MCS for each user. Weighted sum rate maximization is also considered, and qualification of throughput difference between two strategies is performed. In this process, it is shown that allocating the user powers in direct proportional to user weights asymptotically maximizes weight sum rate. The goal of this paper is to investigate the performance and complexity of state -of-the - art methods for calculation of precoding vectors such as zero –forcing (ZF) or mean square error (MMSE) and Dirty paper Coding(DPC).

Paper Nr: 4

Urban Scale Dissemination in Mobile Pervasive Computing Environments


Alistair Morris, Mélanie Bouroche and Vinny Cahill

Abstract: Smart cities applications become realised through cities becoming equipped with numerous mobile pervasive heterogeneous sensors that produce context data, such as air quality indexes and real time traffic conditions. The consumption of this context enables us to better manage and optimise all aspects of the city. However the dissemination of context data from sensors to such applications at an urban scale across heterogeneous networking environments remains a research challenge. We group existing work group into four categories: flooding-based, gossip-based selection-based or hybrid-based methods. However none of these techniques can enable context dissemination that incorporates mobile context producers or consumers at an urban scale across pervasive heterogeneous networking environments due to the incurred overhead. A divergence between the delivery of context data consumed by applications and context data used by context dissemination network to ensure its delivery exists. We therefore consider hybrid techniques and devise a number of novel approaches. We plan to validate our claim that a hybrid approach enables urban scalability through results gained through extensive simulations.