Spectral Emission Mask Shaping for OFDM in Cognitive Radios

Orthogonal frequency division multiplexing (OFDM) is characterized by spectral efficiency. It enables flexible and agile spectrum allocation. But still it lags as it suffers from spectral leakage in the form of large side lobes. It leads to inter-channel interference if not handled carefully.in proposed system spectral emission mask system is implemented to combat spectral leakage and ultimately avoiding adjacent channel interference. A spectral mask, also known as a channel mask or transmission mask is a mathematically-defined set of lines applied to the levels of radio (or optical) transmissions. The spectral mask is generally intended to reduce adjacent-channel interference by limiting excessive radiation at frequencies beyond the necessary bandwidth. The proposed system is implemented over MATLAB platform using script language.

An Efficient Data Transmission in Cognitive Radio Networks Using Momentum Search Algorithm

Data Transmission plays an important role in the digital world. In here, We are using Cognitive Radio(CR) a concept on Wireless Sensor Networks(WSN) which is being used as an intelligent wireless Communication Technology having unique Capabilities of monitoring spectrum bands and detecting available channels to enable the usage of statically allocated spectrum Furthermore, by dynamically adjusting its operating parameters, it can utilize available channels and to attack the upcoming spectrum crunch issue. Cognitive Radios can be used to find unused licensed spectrum and it can be utilized by secondary users without causing any interference to licensed users. Existing technologies used in cognitive radio include energy sensing, spectrum databases, and spectrum sensing using pilot channels. In small networks, transmission of small packet size can be transmitted with high efficiency without delay, whereas transmission of large data packets can cause data corruption, data packet corruption and may require retransmission over higher frequency channels. To avoid this type of interference, users need higher efficiency and wider bandwidth for efficient transmission. Here we use the technique of momentum search algorithms working on the law of conservation of momentum and the law of conservation of kinetic energy. Data transferred using this method is always unaltered. The transmitted data is split into fixed-size 64-bit packets. And the channel selection will be changed accordingly for higher channel selection efficiency for lossless data transmission. The rules of the Momentum Search algorithm allow users to transmit larger data packets with higher efficiency with the same level of interference as the primary user (PU). This proposal shows how to achieve the highest level of data transmission performance using a cognitive wireless network based on a Momentum search algorithm.

Convex Optimisation for Communication Systems

<p>In this thesis new robust methods for the efficient sharing of the radio spectrum for underlay cognitive radio (CR) systems are developed. These methods provide robustness against uncertainties in the channel state information (CSI) that is available to the cognitive radios. A stochastic approach is taken and the robust spectrum sharing methods are formulated as convex optimisation problems. Three efficient spectrum sharing methods; power control, cooperative beamforming and conventional beamforming are studied in detail. The CR power control problem is formulated as a sum rate maximisation problem and transformed into a convex optimisation problem. A robust power control method under the assumption of partial CSI is developed and also transformed into a convex optimisation problem. A novel method of detecting and removing infeasible constraints from the power allocation problem is presented that results in considerably improved performance. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations. The concept of cooperative beamforming for spectrum sharing is applied to an underlay CR relay network. Distributed single antenna relay nodes are utilised to form a virtual antenna array that provides increased gains in capacity through cooperative beamforming. It is shown that the cooperative beamforming problems can be transformed into convex optimisation problems. New robust cooperative beamformers under the assumption of partial and imperfect CSI are developed and also transformed into convex optimisation problems. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations. Conventional beamforming to allow efficient spectrum sharing in an underlay CR system is studied. The beamforming problems are formulated and transformed into convex optimisation problems. New robust beamformers under the assumption of partial and imperfect CSI are developed and also transformed into convex optimisation problems. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations.</p>

Convex Optimisation for Communication Systems

<p>In this thesis new robust methods for the efficient sharing of the radio spectrum for underlay cognitive radio (CR) systems are developed. These methods provide robustness against uncertainties in the channel state information (CSI) that is available to the cognitive radios. A stochastic approach is taken and the robust spectrum sharing methods are formulated as convex optimisation problems. Three efficient spectrum sharing methods; power control, cooperative beamforming and conventional beamforming are studied in detail. The CR power control problem is formulated as a sum rate maximisation problem and transformed into a convex optimisation problem. A robust power control method under the assumption of partial CSI is developed and also transformed into a convex optimisation problem. A novel method of detecting and removing infeasible constraints from the power allocation problem is presented that results in considerably improved performance. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations. The concept of cooperative beamforming for spectrum sharing is applied to an underlay CR relay network. Distributed single antenna relay nodes are utilised to form a virtual antenna array that provides increased gains in capacity through cooperative beamforming. It is shown that the cooperative beamforming problems can be transformed into convex optimisation problems. New robust cooperative beamformers under the assumption of partial and imperfect CSI are developed and also transformed into convex optimisation problems. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations. Conventional beamforming to allow efficient spectrum sharing in an underlay CR system is studied. The beamforming problems are formulated and transformed into convex optimisation problems. New robust beamformers under the assumption of partial and imperfect CSI are developed and also transformed into convex optimisation problems. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations.</p>

Power Control for Cognitive Radio Networks: A Game Theoretic Approach

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.

An Intelligent cognitive sensing and detection strategy for medical telemetry networks

In medical telemetry networks, cognitive radio technology is mostly used to avoid licensed spectrum underutilization and by providing access to unlicensed spectrum users without causing interference to primary users, this concept is widely used in development of smart hospitals and smart cities. In medical telemetry networks frequency spectrum concept is used for providing treatment to patients who are far away from hospitals. In cognitive radios, spectrum sensing concept is used in which energy detection method is mostly used because it is simple to implement. While measuring health care environments using cognitive radios probability detection, false alarm probability and threshold parameters are calculated. In this paper for identifying spectrum holes in spectrum sensing using energy detection, distributed diffusion non-negative least mean square algorithm is proposed. It gives better results compared to energy detection concept alone in terms of probability detection converged earlier. If number of nodes are increasing probability detection is decreased from one and move towards left and its SNR is around 1.5-2 dB with proposed method. Hence simulation results give better results in terms of sensing ability while measuring patient condition.