Avik Banerjee

Fuzzy C-Means Clustering in Energy Detection for Cooperative Spectrum Sensing in Cognitive Radio System

An energy detection based cooperative spectrum sensing approach using Fuzzy c-means clustering is proposed in this work for cognitive radio system. The objective here is to categorize first the measured PU energy contents into multiple classes to highlight the relative degree in presence or absence of PU and Fuzzy c-means (FCM) algorithm is utilized for this purpose. A soft decision based spectrum sensing is proposed here to categorize the presence or absence of PU in four different classes which then develop individual binary decision functions. Resultant binary decision function is then developed using OR fusion rule. Simulation results highlight that the proposed scheme provides high detection probability at low diversity and less number of samples. The results are further compared with the performance of the conventional energy detector methods to highlight the significance of the proposed scheme.

Joint Power Allocation and Route Selection for Outage Minimization in Multihop Cognitive Radio Networks with Energy Harvesting

This paper explores joint power allocation and route selection in a multihop cognitive radio network consisting of secondary transmitter and receiver connected through decode-and-forward relays. A novel frame structure of radio frequency energy harvesting (EH)-cooperation-transmission is considered that operates in time switching mode. The relays also help (cooperation phase) in data transmission between the primary transmitter and receiver using a fraction of the harvested energy. An optimization problem is formulated to minimize the end-to-end secondary outage probability under the constraints of energy causality and primary user cooperation rate. Closed form expressions of the optimal time duration for EH and power allocation factor on each relay are also derived. In order to minimize the total power consumption (cost) and to enhance the network lifetime, the optimal route selection is also explored using Bellman-Ford algorithm and the efficacy of the same over Dijkstra’s algorithm is also demonstrated by a large set of simulation results. Simulation results also show that a gain in outage probability ~43.57% and ~56.66% is achieved for the proposed approach over the existing works.

On Residual Energy Maximization in Energy Harvesting Cognitive Radio Network

Recent advancement in wireless communications demands high data rate transmission at low power consumption. To this aim, the present work proposes an energy harvesting based cognitive radio (CR) system operating in time slotted mode. Energy harvesting and spectrum sensing (SS) are done simultaneously by the CR user through power splitting mode. On the other hand, during the transmission time slot, the CR user either harvests energy or transmits its own data based on SS decision result. An optimization problem is developed to maximize the residual energy under the constraints of sensing reliability of the PU and spectrum efficiency (SE) target rate of the CR. The concavity of the objective function is shown which ensures a global solution to the problem. Closed form expressions for the sensing time and CR transmit power are found and the results are validated by simulations.

Energy detection based cooperative spectrum sensing using fuzzy conditional entropy maximization

An Energy detection based cooperative spectrum sensing for cognitive radio system is proposed in this paper using fuzzy conditional entropy maximization. Instead of using conventional single threshold in energy value, this paper deals with utilization of multiple thresholds to improve the sensing reliability. The basic objective here is to calculate an optimal set of fuzzy parameters that would maximize the fuzzy conditional entropy and Differential Evolution algorithm is used for this purpose. Multiple threshold values are calculated using these optimal parameters. Simulation results highlight improved performance of the proposed scheme by providing high detection probability at low diversity and using less number of samples. Performance results are compared with the conventional cooperative energy detector methods to highlight the significance of the proposed scheme.

On optimal sample checkpoint for energy efficient cooperative spectrum sensing

Abstract Energy efficient and fast yet reliable spectrum sensing in cognitive radio networks (CRNs) is an important issue and is often met through the involvement of (optimal) multiple sensing nodes in collaboration known as cooperative spectrum sensing (CSS). However, due to severe fading, sometimes transmission of sensing samples over some reporting channels (R-channels) consume much energy but contribute very little on global sensing decision. To address the problem, this work explores the scope of using an optimal checkpoint to stop further transmission of sensing samples over the deeply faded R-channels. First an energy minimization problem under the constraints of detection and false alarm probabilities is developed in an amplify forward relay assisted CSS system in terms of optimal sample checkpoint, the number of essential sensing/relay nodes and relay power gain. The problem is further extended in presence of primary user emulation attack (PUEA). Simulation results show that a performance gain ∼77.17% and ∼71.25% in energy consumption can be achieved for the proposed approach as compared to the existing two works at P d = 0.9 and P f = 0.05 .

On outage minimization in relay assisted cognitive radio networks with energy harvesting

Abstract This paper considers a fully energy harvested two hop relay assisted cognitive radio (CR) system operated in an underlay mode. The frame structure of the CR network consists of three non-overlapping time slots. The first time slot is meant for energy harvesting (EH) at the relay node (from both the primary interference signal and the secondary transmitter signal), while during the second slot, the secondary user transmits its data to the relay (information transmission). During the third time slot, forwarding of data by the relay and EH at secondary transmitter (from the primary interference signal) are done simultaneously. An optimization problem is formulated that minimizes the outage probability under the constraints of maintaining the energy causality and interference threshold to the primary receiver due to both the secondary transmitter and the relay node. Closed form expressions for the optimal transmit power of the source and the relay node as well as the time slot for EH are derived. The convexity of the constrained objective function is proved mathematically and the analytical solutions are verified through a large set of simulation results. Simulation results also show that a gain  ∼  11.71% and  ∼  12.7% in outage probability minimization is achieved for the proposed scheme over the existing works.

On outage secrecy minimisation in an energy harvesting relay assisted cognitive radio networks

This work considers an energy harvesting (EH) based two-hop relay assisted cognitive radio system that consists of a secondary transmitter, a relay node and a cooperative jammer operated in an underlay mode with a primary transmitter–receiver pair. An optimisation problem is formulated to minimise the secrecy outage probability under the constraints of simultaneously meeting the energy causality of the secondary transmit nodes, interference to the primary receiver and secondary outage probability. An analytical expression of the secrecy outage probability is developed followed by deriving the closed-form expressions to determine the optimal transmit power of the source, the relay node and the fraction of the time slot for EH. Simulation results show that the minimum value of the secrecy outage probability is ∼ 6.4 % and ∼ 19.18 % less over the existing works.

Residual energy maximization in cooperative spectrum sensing with energy harvesting

This paper considers a cooperative spectrum sensing scheme for cognitive radio network that uses a power splitting mode for simultaneous sensing and harvesting of energy. The objective is to maximize the residual harvested energy over the total energy consumption in the sensing process. An optimization problem is formulated in terms of the number of secondary user (sensing) nodes, the number of samples required, amplifying gain for transmission of samples and power splitting factor under the constraints of detection and false alarm probabilities. The concavity of the constrained objective function is proved mathematically and the analytical solutions are verified through a large set of simulation results. Simulation result shows that 40% gain in residual energy is achieved over the existing work at detection and false alarm probabilities of 0.9 and 0.05, respectively.

On energy minimization in cooperative spectrum sensing using LRT in presence of emulation attack

Energy efficient and reliable spectrum sensing become essential in cooperative cognitive radio networks. However, cooperation in spectrum sensing (SS) is often vulnerable to several security threats; one such operation is primary user emulation attack (PUEA). To address the issues, an optimization framework is developed in this work to minimize the energy consumption in cooperative spectrum sensing (CSS) in presence of PUEA using log-likelihood ratio test (LLRT) at the fusion center (FC) while maintaining a target sensing reliability. Sensing reliability is characterized by a high detection probability and a low false alarm probability. FC is assumed to be equipped with multiple antennas, where each one receives signal from a particular secondary user along-with PUEA signal. FC computes a global test statistics by combining all log-likelihood ratios (LLRs). Simulation results highlight performance gain in energy consumption at low sensing duration over the existing energy detection based approach.