Efficient Channel Allocation using Matching Theory for QoS Provisioning in Cognitive Radio Networks.

The focus of research efforts in cognitive radio networks (CRNs) has primarily remained confined to maximizing the utilization of the discovered resources. However, it is also important to enhance the user satisfaction in CRNs by finding a suitable match between the secondary users and the idle channels available from the primary network while taking into consideration not only the quality of service (QoS) requirements of the secondary users but the quality of the channels as well. In this work, the Gale Shapley matching theory was applied to find the best match, so that the most suitable channels from the available pool were allocated that satisfy the QoS requirements of the secondary users. Before applying matching theory, two objective functions were defined from the secondary user's perspective as well as from the channel's perspective. The objective function of secondary users is the weighted sum of the data rate of the secondary users and the probability of reappearance of the primary user on the channel. Whereas, the objective function of the channel is the maximum utilization of the channel. The weight factors included in the objective functions allow for diverse service classes of secondary users (SUs) or varying channel quality characteristics. The objective functions were used in developing the preference lists for the secondary users and the idle channels. The preference lists were then used by the Gale Shapely matching algorithm to determine the most suitably matched SU-channel pairs. The performance of the proposed scheme was evaluated using Monte-Carlo simulations. The results show significant improvement in the overall satisfaction of the secondary users with the proposed scheme in comparison to other contemporary techniques. Further, the impact of changing the weight factors in the objective functions on the secondary user's satisfaction and channel utilization was also analyzed.

Analysis of Efficient Spectrum Handoff in a Multi-Class Hybrid Spectrum Access Cognitive Radio Network Using Markov Modelling.

Cognitive radio networks (CRNs) rely on sensing of the licensed spectrum of a primary network to dynamically ascertain underutilized portion of the spectrum, thus affording additional communication opportunities. In a CRN, a single homogeneous spectrum access, such as interweave only deprives the secondary users (SUs) of channel access during handoff, particularly at high primary network traffic. Therefore, providing quality-of-service (QoS) to multi-class SUs with diverse delay requirements during handoff becomes a challenging task. In this paper, we have evolved a Markov-based analytical model to ascertain the gain in non-switching spectrum handoff scheme for multi-class SUs employing hybrid interweave-underlay spectrum access strategy. To satisfy the QoS requirements of the delay-sensitive traffic, we have analyzed the impact of hybrid spectrum access scheme for prioritized multi-class SUs traffic. The results show substantial improvement in spectrum utilization, average system throughput and extended data delivery time compared to conventional CRN using interweave only spectrum access. This demonstrates the suitability of the proposed scheme towards meeting QoS requirements of the delay-sensitive SU traffic while improving the overall performance for delay-tolerant SU traffic as well.

Spectrum Handoff based on Imperfect Channel State Prediction Probabilities with Collision Reduction in Cognitive Radio Ad Hoc Networks.

The spectrum handoff is highly critical as well as challenging in a cognitive radio ad hoc network (CRAHN) due to lack of coordination among secondary users (SUs), which leads to collisions among the SUs and consequently affects the performance of the network in terms of spectrum utilization and throughput. The target channel selection mechanism as part of handoff process can play an enormously significant role in minimizing the collisions among the SUs and improving the performance of a cognitive radio network (CRN). In this paper, an enhanced target channel selection scheme based on imperfect channel state prediction is proposed for the spectrum handoff among the SUs in a CRAHN. The proposed scheme includes an improved frame structure that increases coordination among the SUs in the ad hoc environment and helps in organizing the SUs according to the shortest job first principle during channel access. Unlike the existing prediction-based spectrum handoff techniques, the proposed scheme takes into account the accuracy of channel state prediction; the SUs affected due to false prediction are compensated by allowing them to contend for channel access within the same transmission cycle and thus enabling them to achieve higher throughput. The proposed scheme has been compared with the contemporary spectrum handoff schemes and the results have demonstrated substantial improvement in throughput and extended data delivery time by virtue of the reduced number of collisions.

Resurrection of carbon dioxide as refrigerant in solar thermal absorption cooling systems.

The existing air conditioning and cold storage systems use conventional compressor based systems, compelling more electricity and greenhouse gasses (GHG) emissions. The incumbent cooling system uses synthetic refrigerants (CFCs, HCFC, and HFCs) that outperform natural refrigerants but are banned or under time bared permission due to their harmful effects. The global community of (196 parties till 2017) has ratified Paris Accord to limit GHG emissions and use low Global Warming Potential (GWP) refrigerants, and after the ban on existing synthetic refrigerants, quested for suitable natural working fluids and retrofitting in the existing system. Among ASHRAE envisaged natural refrigerants, CO2 has resurrected as an emerging refrigerant after the availability of high pressure technologies. The proposed design of solar assisted absorption chiller employing CO2 as a heat transfer fluid for a commercial dwelling is simulated for a dwelling in the hot and humid, moderate and sun adverse region (Lahore, 31.5204° N, 74.3587° E) to assess the thermal properties of the proposed design. A thermal storage tank with immersed heat exchangers augmented to meet the intermittency of solar energy. A solar evacuated glass tube collector (EGTC) with U-shaped copper tubes is used to collect solar heat energy. Integration of renewable energy (RE) systems is inevitable due to the persistent energy crisis and climate change situations. Solar energy is a promising source of energy abundantly available in hot areas. CO2 is a natural refrigerant that outperforms ASHRAE envisaged natural refrigerants due to the low critical point. A solar thermal cooling system employing a 35.2 kW absorption chiller driven via heat energy harnessed with EGTC using R-744 supported by an auxiliary furnace is simulated in a TRNSYS® Simulation environment. The simulated system covers the cooling requirements of a large three-room dwelling in Lahore, Pakistan. The proposed design comprises an R-744-based solar heating system combined with a hot water-fired absorption chiller. The results were dynamically simulated for the hot climate of Lahore, Pakistan, with average yearly maintained temperatures of 23 °C, 26 °C, and 21 °C for the three rooms and 0.21 solar fraction for the whole year.