Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

An Improvement of Subject Reacquisition by Reasoning and Revision

CCTV systems are broadly deployed in the present world. Despite this, the impact on anti-social and criminal behaviour has been minimal. Subject reacquisition is a fundamental task to ensure in-time reaction for intelligent surveillance. However, traditional reacquisition based on face recognition is not scalable, hence in this paper we use reasoning techniques to reduce the computational effort which deploys the time-of-flight information between interested zones such as airport security corridors. Also, to improve accuracy of reacquisition, we introduce the idea of revision as a method of post-processing.We demonstrate the significance and usefulness of our framework with an experiment which shows much less computational effort and better accuracy.

Comparative Raman Study of Carbon Nanotubes Prepared by D.C. Arc Discharge and Catalytic Methods

The Raman spectra of carbon nanotubes prepared by catalytic (C-CNT) and d.c. arc discharge (D-CNT) methods are reported. A previously unnoticed third-order Raman peak at ca. 4248 cm-1 was observed in the Raman spectrum of D-CNT. The Raman features of D-CNT and C-CNT are similar to those of highly oriented pyrolytic graphite (HOPG) and active carbon, respectively. The data also suggest that the increase in disorder in D-CNT compared with HOPG is due to structural defects in D-CNT. © 1997 by John Wiley & Sons, Ltd.