246,174 research outputs found
Development and demonstration of a renewable energy based demand/supply decision support tool for the building design profession
Future cities are likely to be characterised by a greater level of renewable energy systems deployment. Maximum impact will be achieved when such systems are used to offset local energy demands in contrast to current philosophy dictating the grid connection of large schemes. This paper reports on the development of a software tool, MERIT, for demand/ supply matching. The purpose of MERIT is to assist with the deployment of renewable energy systems at all scales. This paper describes the procedures used to match heterogeneous supply technologies to a set of demand profiles corresponding to the different possible fuel types
Resource allocation in OFDMA networks with half-duplex and imperfect full-duplex users
Recent studies indicate the feasibility of in-band fullduplex (FD) wireless
communications, where a wireless radio transmits and receives simultaneously in
the same band. Due to its potential to increase the capacity, analyzing the
performance of a cellular network that contains full-duplex devices is crucial.
In this paper, we consider maximizing the weighted sum-rate of downlink and
uplink of a single cell OFDMA network which consists of an imperfect FD
base-station (BS) and a mixture of half-duplex and imperfect full-duplex mobile
users. To this end, the joint problem of sub-channel assignment and power
allocation is investigated and a two-step solution is proposed. A heuristic
algorithm to allocate each sub-channel to a pair of downlink and uplink users
with polynomial complexity is presented. The power allocation problem is
convexified based on the difference of two concave functions approach, for
which an iterative solution is obtained. Simulation results demonstrate that
when all the users and the BS are perfect FD nodes the network throughput could
be doubled, Otherwise, the performance improvement is limited by the inter-node
interference and the self-interference. We also investigate the effect of the
self-interference cancellation capability and the percentage of FD users on the
network performance in both indoor and outdoor scenarios.Comment: 6 pages, 8 figures, Accepted in IEEE International Conference on
Communication (ICC), Malaysia, 201
Generating Levels That Teach Mechanics
The automatic generation of game tutorials is a challenging AI problem. While
it is possible to generate annotations and instructions that explain to the
player how the game is played, this paper focuses on generating a gameplay
experience that introduces the player to a game mechanic. It evolves small
levels for the Mario AI Framework that can only be beaten by an agent that
knows how to perform specific actions in the game. It uses variations of a
perfect A* agent that are limited in various ways, such as not being able to
jump high or see enemies, to test how failing to do certain actions can stop
the player from beating the level.Comment: 8 pages, 7 figures, PCG Workshop at FDG 2018, 9th International
Workshop on Procedural Content Generation (PCG2018
SciTech News Volume 71, No. 2 (2017)
Columns and Reports From the Editor 3
Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division 9 Aerospace Section of the Engineering Division 12 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 14
Reviews Sci-Tech Book News Reviews 16
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Development of a simulation-based decision support tool for renewable energy integration and demand-supply matching
This paper describes a simulation-based decision support tool, MERIT, which has been developed to assist in the assessment of renewable energy systems by focusing on the degree of match achievable between energy demand and supply. Models are described for the prediction of the performance of PV, wind and battery technologies. These models are based on manufacturers' specifications, location-related parameters and hourly weather data. The means of appraising the quality of match is outlined and examples are given of the application of the tool at the individual building and community levels
High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation
In this paper, we present a low-complexity algorithm for detection in
high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that
achieve high spectral efficiencies of the order of tens of bps/Hz. We also
present a training-based iterative detection/channel estimation scheme for such
large STBC MIMO systems. Our simulation results show that excellent bit error
rate and nearness-to-capacity performance are achieved by the proposed
multistage likelihood ascent search (M-LAS) detector in conjunction with the
proposed iterative detection/channel estimation scheme at low complexities. The
fact that we could show such good results for large STBCs like 16x16 and 32x32
STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in
excess of 20 bps/Hz (even after accounting for the overheads meant for pilot
based training for channel estimation and turbo coding) establishes the
effectiveness of the proposed detector and channel estimator. We decode perfect
codes of large dimensions using the proposed detector. With the feasibility of
such a low-complexity detection/channel estimation scheme, large-MIMO systems
with tens of antennas operating at several tens of bps/Hz spectral efficiencies
can become practical, enabling interesting high data rate wireless
applications.Comment: v3: Performance/complexity comparison of the proposed scheme with
other large-MIMO architectures/detectors has been added (Sec. IV-D). The
paper has been accepted for publication in IEEE Journal of Selected Topics in
Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO
Systems. v2: Section V on Channel Estimation is update
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