A MAC Layer Protocol For Smart Indoor Inventory Management System

The indoor inventory system is gaining more research attention and commercial value with the development of IoT. In this thesis, we presented the design of a MAC protocol that allows synchronized transmission of location and sensing data in a wireless positioning and sensor network for an indoor inventory system. The network supports real-life industrial applications and provides a highly specific positioning method.<div>In the network, mobile sensing tags are connected to smart readers that performs localization of tags and gathers sensing data from the tags. The readers are connected to the back-end cloud. The proposed MAC serves multiple classes of mobile tags with different priorities and latency requirements. These tags transmit critical, position and sensing data with different QoS requirements. The proposed MAC is a hybrid MAC that offers contention-based period for tag discovery and scheduled period for the transmission of sensing data with guaranteed latency. We conducted simulation to evaluate the performance of different methods of discovery process and their impact on latency assurance. We also developed a queuing model to analyze the relationship between parameters, acquiring parameters through experiment, and calculation of boundary values.<br></div><div>Simulation using MatLabTM software suggests that the joining period in design can increase the transmission success rate of high priority messages at the cost of a slight increment in the delay of low priority messages. Preliminary analysis suggests that by adaptively allocating the channel resources of the network to three types of tags, service efficiency can be improved. This result also guides the direction for further improvement.<br></div><div>We explored the performance of two options considered currently, which is selecting the discovery process according to modulo result of unique 16-bit tag ID and random select of an available discovery process. In the current environment where each tag does not have any information about other tags inside the network, the two methods have the same effect on avoiding collisions that could happen in a single discovery cycle.<br></div><div>The proposed MAC layer protocol can provide the best service when the available discovery process in the discovery cycle is for initialization and resetting. For an emergency, the joining period designs can still ensure a success rate for critical messages to be over 90%. Hence, the simulation results indicate the joining period method is able to improve MAC-layer performance.</div><div> <br></div>

A MAC Layer Protocol For Smart Indoor Inventory Management System

The indoor inventory system is gaining more research attention and commercial value with the development of IoT. In this thesis, we presented the design of a MAC protocol that allows synchronized transmission of location and sensing data in a wireless positioning and sensor network for an indoor inventory system. The network supports real-life industrial applications and provides a highly specific positioning method.<div>In the network, mobile sensing tags are connected to smart readers that performs localization of tags and gathers sensing data from the tags. The readers are connected to the back-end cloud. The proposed MAC serves multiple classes of mobile tags with different priorities and latency requirements. These tags transmit critical, position and sensing data with different QoS requirements. The proposed MAC is a hybrid MAC that offers contention-based period for tag discovery and scheduled period for the transmission of sensing data with guaranteed latency. We conducted simulation to evaluate the performance of different methods of discovery process and their impact on latency assurance. We also developed a queuing model to analyze the relationship between parameters, acquiring parameters through experiment, and calculation of boundary values.<br></div><div>Simulation using MatLabTM software suggests that the joining period in design can increase the transmission success rate of high priority messages at the cost of a slight increment in the delay of low priority messages. Preliminary analysis suggests that by adaptively allocating the channel resources of the network to three types of tags, service efficiency can be improved. This result also guides the direction for further improvement.<br></div><div>We explored the performance of two options considered currently, which is selecting the discovery process according to modulo result of unique 16-bit tag ID and random select of an available discovery process. In the current environment where each tag does not have any information about other tags inside the network, the two methods have the same effect on avoiding collisions that could happen in a single discovery cycle.<br></div><div>The proposed MAC layer protocol can provide the best service when the available discovery process in the discovery cycle is for initialization and resetting. For an emergency, the joining period designs can still ensure a success rate for critical messages to be over 90%. Hence, the simulation results indicate the joining period method is able to improve MAC-layer performance.</div><div> <br></div>

A Spreading Factor Congestion Status-Aware Adaptive Data Rate Algorithm

LoRaWAN has established itself as one of the leading MAC layer protocols in the field of LPWAN. Although the technology itself is quite mature, its resource allocation mechanism, the Adaptive Data Rate (ADR) algorithm is still quite new, unspecified and its functionalities still limited. Various studies have shown that the performance of the ADR algorithm gradually suffers in dense networks. Recent studies and proposals have been made as attempts to improve the algorithm. In this paper, the authors proposed a spreading factor congestion status aware ADR version and compared its performance against that of four other related algorithms to study the performance improvements the algorithm brings to LoRaWAN in terms of DER and EC. LoRaSim was used to evaluate the algorithms’ performances in a simple sensing application that involved end devices transmitting data to the gateway every hour. The performances were measured based on how they affected DER as the network size increases. The results obtained show that the proposed algorithm outperforms the currently existing implementations of the ADR in terms of both DER and EC. However, the proposed algorithm is slightly outperformed by the native ADR in terms of EC. This was expected as the algorithm was mainly built to improve DER. The proposed algorithm builds on the existing algorithms and the ADR and significantly improves them in terms of DER and EC (excluding the native ADR), which is a significant step towards an ideal implementation of LoRaWAN’s ADR.

Guided MAC to Enhance Quality of Experience of Video Data Transmission over Massive MIMO

Massive MIMO (M-MIMO) system comprises of multiple number of antennas to achieve energy- efficiency and large gains in spectral-efficiency in comparison to existing MIMO technology. High speed and Quality of Experience (QoE) of video data over wireless communication has always been a challenge for the researchers due to scarcity of the bandwidth, fading and interference. The channels with high noise corrupt the transmitted video and results in poor QoE of at the receiver. Therefore, to maintain the quality of transmitted video, it is highly desirable to identify noisy channels and avoid transmission over them. This paper deals with QoE of the transmitted video over Massive MIMO channels. The channels are categorized into two categories: good and bad depending upon the value of Signal to Interference and Noise Ratio (SINR). A channel above the minimum acceptable value (threshold) of SINR is categorized as good channel otherwise bad channel. A Guided MAC layer (GMAC) protocol is designed to transmit the video data over good channels only and to discard the transmission over bad channels.