The multiple-input multiple-output (MIMO) performance of the modulated scattering antenna array (MSAA) is analyzed numerically for the first time in indoor environment based on an approach to hybridization of the Volterra series method and method of moments (MoM) in this letter. Mutual coupling effect between the Modulated scattering element (MSE) and the normal antenna element is also considered in this analysis. It is found that MIMO performance of the MSAA is improved with reducing the array spacing of the MSAA in 4 different indoor receiving areas. At the same time, the simulated results of the MSAA are compared with those of the dipole antenna array at the same condition.

With proliferation of smart handsets capable of mobile Internet, the severity of malware attacks targeting such handsets is rapidly increasing, thereby requiring effective countermeasure for them. However, existing signature-based solutions are not suitable for resource-poor handsets due to the excessive run-time overhead of matching against ever-increasing malware pattern database as well as the limitation of detecting well-known malware only. To overcome these drawbacks, we present a bio-inspired approach to discriminate malware (non-self) from normal programs (self) by replicating the processes of biological immune system. Our proposed approach achieves superior performance in terms of detecting 83.7% of new malware or their variants and scalable storage requirement that grows very slowly with inclusion of new malware, making it attractive for use with mobile handsets.