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This paper studies the performance of joint Vertical Bell Laboratories layered space-time architecture (VBLAST)/Space-Time Block Coding (STBC) aided multipleinput multiple-output (MIMO) system in a multi-cell multi-user setting with multi-user transmitter preprocessing (MUTP) based on singular value decomposition (SVD), which exploits the channel state information (CSI) of all the users at the base stations (BSs) and only individual user's CSI at the mobile stations (MS) for downlink (DL) communication. Specifically, in this contribution, in contrast to previous work [6], we study the effects of four types of delay spread on MUTP assisted joint VBLAST/STBC MIMO system over correlated and uncorrelated frequency-selective channels. In a multi-cell scenario, in addition to multi stream interference (MSI) and multi-user interference (MUI), users conflict co-channel interference (CCI) which can severely degrade the system performance. Simulation studyshows that MUTP can mitigate CCI and MSI with less detection complexity. Comparisons for correlated and uncorrelated frequency-selective channels with and without MUTP are also provided. Keywords-Multiple-input multiple-output(MIMO); preprocessing; post-processing; multi-user transmitter preprocessing (MUTP); singular value decomposition (SVD); cochannel interference (CCI); multi-user interference (MUI); multi stream interference (MSI).

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In the modern era, the escalation of vehicles on the roads has caused an increasin g need for a reliable and intelli g ent control of the traffic li g ht system. This paper is aimed at solvin g this crisis by effectively computin g the density of traffic based on the ima g es picked up by cameras placed on the traffic posts. The method involves a simple al g orithm which performs pixel elimination and detection followed by processin g usin g a fuzzy controller. It can be further extended towards hardware implementation usin g dedicated processors. Our approach involves takin g ima g es at re g ular intervals and continuously processin g them with a reference ima g e which is captured when there is no traffic (empty road).The reference ima g es are stored and used for calibration purpose. This al g orithm enables the system to infer the traffic density which is then evaluated by a fuzzy controller to determine the timin g of the traffic si g nals. The fuzzy controller consists of an output function which dynamically controls the output based on the comparison of current ima g e's pixel count correspondin g to the vehicle density.Index Terms-Fuzzy controller, Pixel elimination and detection al g orithm, output distribution function.