24,883 research outputs found
Multi-Antenna Assisted Virtual Full-Duplex Relaying with Reliability-Aware Iterative Decoding
In this paper, a multi-antenna assisted virtual full-duplex (FD) relaying
with reliability-aware iterative decoding at destination node is proposed to
improve system spectral efficiency and reliability. This scheme enables two
half-duplex relay nodes, mimicked as FD relaying, to alternatively serve as
transmitter and receiver to relay their decoded data signals regardless the
decoding errors, meanwhile, cancel the inter-relay interference with
QR-decomposition. Then, by deploying the reliability-aware iterative
detection/decoding process, destination node can efficiently mitigate
inter-frame interference and error propagation effect at the same time.
Simulation results show that, without extra cost of time delay and signalling
overhead, our proposed scheme outperforms the conventional selective
decode-and-forward (S-DF) relaying schemes, such as cyclic redundancy check
based S-DF relaying and threshold based S-DF relaying, by up to 8 dB in terms
of bit-error-rate.Comment: 6 pages, 4 figures, conference paper has been submitte
Symbol-Level Selective Full-Duplex Relaying with Power and Location Optimization
In this paper, a symbol-level selective transmission for full-duplex (FD)
relaying networks is proposed to mitigate error propagation effects and improve
system spectral efficiency. The idea is to allow the FD relay node to predict
the correctly decoded symbols of each frame, based on the generalized square
deviation method, and discard the erroneously decoded symbols, resulting in
fewer errors being forwarded to the destination node. Using the capability for
simultaneous transmission and reception at the FD relay node, our proposed
strategy can improve the transmission efficiency without extra cost of
signalling overhead. In addition, targeting on the derived expression for
outage probability, we compare it with half-duplex (HD) relaying case, and
provide the transmission power and relay location optimization strategy to
further enhance system performance. The results show that our proposed scheme
outperforms the classic relaying protocols, such as cyclic redundancy check
based selective decode-and-forward (S-DF) relaying and threshold based S-DF
relaying in terms of outage probability and bit-error-rate. Moreover, the
performances with optimal power allocation is better than that with equal power
allocation, especially when the FD relay node encounters strong
self-interference and/or it is close to the destination node.Comment: 34 pages (single-column), 14 figures, 2 tables, accepted pape
Differentially Coherent Code Acquisition in the MIMO-Aided Multi-Carrier DS-CDMA Downlink
Both differentially coherent and non-coherent code acquisition schemes designed for the multiple-input multiple-output (MIMO)-aided multi-carrier (MC)-DS-CDMA downlink are analysed, when communicating over uncorrelated Rayleigh channels. The attainable mean acquisition time (MAT) performance is studied as a function of both the number of multiple transmit/multiple receive antennas and that of the number of subcarriers. It is demonstrated that in contrast to the expectations, when the number of multiple transmit antennas and/or that of the subcarriers is increased in both the differentially coherent and the non-coherent code acquisition scenarios, the achievable MAT deteriorates over the entire signal-to-interference plus noise ratio (SINR) per chip (Ec/Io) range considered, except for the scenario of single-carrier (SC)-DS-CDMA using P ¼ 2 transmit antennas and R ¼ 1 receive antenna. As expected, the degree of performance degradation depends upon the specific scheme and the Ec/Io ratio considered, although paradoxically, the correctly synchronised MIMO-aided system is capable of attaining its target bit error ratio performance at reduced SINR values
Bit error performance of diffuse indoor optical wireless channel pulse position modulation system employing artificial neural networks for channel equalisation
The bit-error rate (BER) performance of a pulse position modulation (PPM) scheme for non-line-of-sight indoor optical links employing channel equalisation based on the artificial neural network (ANN) is reported. Channel equalisation is achieved by training a multilayer perceptrons ANN. A comparative study of the unequalised `soft' decision decoding and the `hard' decision decoding along with the neural equalised `soft' decision decoding is presented for different bit resolutions for optical channels with different delay spread. We show that the unequalised `hard' decision decoding performs the worst for all values of normalised delayed spread, becoming impractical beyond a normalised delayed spread of 0.6. However, `soft' decision decoding with/without equalisation displays relatively improved performance for all values of the delay spread. The study shows that for a highly diffuse channel, the signal-to-noise ratio requirement to achieve a BER of 10−5 for the ANN-based equaliser is ~10 dB lower compared with the unequalised `soft' decoding for 16-PPM at a data rate of 155 Mbps. Our results indicate that for all range of delay spread, neural network equalisation is an effective tool of mitigating the inter-symbol interference
Stochastic accumulation of feature information in perception and memory
It is now well established that the time course of perceptual processing influences the first second or so of performance in a wide variety of cognitive tasks. Over the last20 years, there has been a shift from modeling the speed at which a display is processed, to modeling the speed at which different features of the display are perceived and formalizing how this perceptual information is used in decision making. The first of these models(Lamberts, 1995) was implemented to fit the time course of performance in a speeded perceptual categorization task and assumed a simple stochastic accumulation of feature information. Subsequently, similar approaches have been used to model performance in a range of cognitive tasks including identification, absolute identification, perceptual matching, recognition, visual search, and word processing, again assuming a simple stochastic accumulation of feature information from both the stimulus and representations held in memory. These models are typically fit to data from signal-to-respond experiments whereby the effects of stimulus exposure duration on performance are examined, but response times (RTs) and RT distributions have also been modeled. In this article, we review this approach and explore the insights it has provided about the interplay between perceptual processing, memory retrieval, and decision making in a variety of tasks. In so doing, we highlight how such approaches can continue to usefully contribute to our understanding of cognition
Exploration and Design of High Performance Variation Tolerant On-Chip Interconnects
Siirretty Doriast
Uncertainty Management and Evidential Reasoning with Structured Knowledge
This research addresses two intensive computational problems of reasoning under uncertainty in artificial intelligence. The first problem is to study the strategy for belief propagation over networks. The second problem is to explore properties of operations which construe the behaviour of those factors in the networks. In the study of operations for computing belief combination over a network model, the computational characteristics of operations are modelled by a set of axioms which are in conformity with human inductive and deductive reasoning. According to different topological connection of networks, we investigate four types of operations. These operations successfully present desirable results in the face of dependent, less informative, and conflicting evidences. As the connections in networks are complex, there exists a number of possible ways for belief propagation. An efficient graph decomposition technique has been used which converts the complicated networks into simply connected ones. This strategy integrates the logic and probabilistic aspects inference, and by using the four types of operations for its computation it gains the advantage of better description of results (interval-valued representation) and less information needed. The performance of this proposed techniques can be seen in the example for assessing civil engineering structure damage and results are in tune with intuition of practicing civil engineers
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