Kiran Sultan

Ambiguity Function of Phased–MIMO Radar With Colocated Antennas and Its Properties

In recent years, multiple-input-multiple-output (MIMO) radar has been receiving increasing attention from researchers due to its numerous benefits. In contrast to conventional radar systems, it offers increased spatial resolution and improved parameter estimation, target tracking, and recognition performance. Recently, a combination of phased-array radar and MIMO radar, which is called Phased-MIMO radar, has also been proposed and studied. The ambiguity function has been a traditional and effective tool to investigate the range and Doppler resolution of conventional radar systems and is now being extended for MIMO radar systems. In this letter, the ambiguity function of the Phased-MIMO radar with overlapping subarrays has been formulated, and some mathematical properties of the ambiguity function have been derived. These properties can help when comparing the performance of conventional and MIMO radar systems. This letter can be considered an extension of the work done by Chen and Vaidyanathan for MIMO radar systems.

SNR maximization through relay selection and power allocation for non-regenerative Cognitive Radio Networks

SNR maximization while adhering to interference constraint towards primary users is a key challenge in Cognitive Radio Networks (CRNs). Cooperative communication is a promising technique to achieve this goal by exploiting spatial diversity. We consider an Amplify-and-Forward based cognitive relay network comprising one source-destination pair and multiple relays in underlay spectrum sharing environment and solve the problem of relay selection and power allocation to the selected relays. In this scenario, we formulate an optimization problem aiming to maximize the signal-to-noise ratio (SNR) at the secondary destination under interference power constraint towards the PU as well as individual relays transmit power constraint. Our relay selection scheme allows more than one relay to cooperate in contrast to single relay selection methods which compromise on spatial diversity. We solve our optimization problem using Artificial Bee Colony (ABC). The proposed algorithm has low computational complexity and its effectiveness is proved through simulation results.

Joint spectrum sensing for detection of primary users using cognitive relays with evolutionary computing

The spectrum sensing is one of the most challenging research fields in cognitive radio networks (CRN). Joint spectrum sensing not only improves the detection performance of the system, but also increases overall agility of the CRN. This study presents a centralised relay-based spectrum sensing technique using hybrid nature based algorithm that detects the number of active primary users and jointly estimates (amplitude, carrier frequency and direction of arrival of far-field sources impinging on uniform linear arrays (ULA) mounted on each relay. The fitness function is a sum of mean square error and the correlation error. All the individual decisions from each relay are passed on to the fusion centre that provides the final decision on the values of the aforementioned parameters. The validity of the proposed scheme is investigated for various SNR levels along with different sizes of ULAs on each relay.

Properties of ambiguity function of frequency diverse array radar

Frequency Diverse Array (FDA) radar has recently gained substantial interest among the researchers due to its unique range-angle-dependent beampattern in contrast to angle-dependent beampattern of phased-array radar. In the simplest form of FDA radar, a uniform inter-element frequency offset is applied across the aperture of uniform linear array of sensors. This offset may be small as compared to the carrier frequency or large, giving rise to different advantages. To investigate the range and Doppler resolution of a radar system, ambiguity function has been a traditional and effective tool. In this letter, the ambiguity function of FDA radar with small frequency offset has been formulated, and some important properties of the ambiguity function have been derived. These properties can help compare its performance with the other forms of radar.

Performance Analysis of Relay Subset Selection Schemes for Underlay Relay-assisted Cognitive Radio Networks (RCRNs)

In underlay cognitive radio networks (CRNs), secondary users (SUs) are allowed to co-exist with the primary users at the cost of reduced transmit power in order to satisfy the stringent interference constraint. This obligation reduces the coverage area of the SUs and they have to involve relaying services for assistance. However, selecting the best combination of relays from the available options is more challenging in an energy-constrained environment, since it is affected not only by the interference constraint, but also the selected subset of relays must guarantee some quality-of-service (QoS) at the secondary destination also. This study is focused on an amplify-and-forward-based relay-assisted CRN operating in an underlay scenario and studies three relay subset selection or multiple relay selection schemes taking into consideration outgoing secondary and primary link qualities of each candidate relay. For each scheme, the closed-form expression for probability density function of signal-to-noise ratio at the secondary destination is derived followed by detailed analysis of two QoS metrics, i.e. outage probability and bit error rate. Finally, simulations have been performed to validate the analytical results.

Performance Enhancement of Underlay Cognitive Radio Networks by Intelligent Multiple Relay Selection

In an underlay spectrum sharing environment, relay selection stands as one of the fascinating techniques to address the challenge of performance enhancement of secondary communication via cognitive relays. In this paper, a similar constrained optimization problem is discussed in which a secondary source-destination pair is assisted by a potential Relay assisted Cognitive Radio (RCRN) in the worst-case scenario when line-of-sight (LOS) path is not available to enable the communication. In order to solve this sophisticated problem, we perform multiple relay selection under the assumption of availability of perfect channel state information (CSI) and propose two novel techniques, one based on Artificial Bee Colony (ABC) evolutionary computing and the second based on Fuzzy Rule Based System (FRBS). Both proposed techniques aim to maximize the signal-to-noise ratio (SNR) at the destination keeping in view the transmit power and interference constraints. The effectiveness of the schemes is highlighted through simulation results, along with their comparison.