Phase space polarization and the topological string: a case study

We review and elaborate on our discussion in hep-th/0606112 on the interplay between the target space and the worldsheet description of the open topological string partition function, for the example of the conifold. We discuss the appropriate phase space and canonical form for the system. We find a map between choices of polarization and the worldsheet description, based on which we study the behavior of the partition function under canonical transformations.Comment: 18 pages, invited review for MPL

Measurement Matrix Design for Compressive Sensing Based MIMO Radar

In colocated multiple-input multiple-output (MIMO) radar using compressive sensing (CS), a receive node compresses its received signal via a linear transformation, referred to as measurement matrix. The samples are subsequently forwarded to a fusion center, where an L1-optimization problem is formulated and solved for target information. CS-based MIMO radar exploits the target sparsity in the angle-Doppler-range space and thus achieves the high localization performance of traditional MIMO radar but with many fewer measurements. The measurement matrix is vital for CS recovery performance. This paper considers the design of measurement matrices that achieve an optimality criterion that depends on the coherence of the sensing matrix (CSM) and/or signal-to-interference ratio (SIR). The first approach minimizes a performance penalty that is a linear combination of CSM and the inverse SIR. The second one imposes a structure on the measurement matrix and determines the parameters involved so that the SIR is enhanced. Depending on the transmit waveforms, the second approach can significantly improve SIR, while maintaining CSM comparable to that of the Gaussian random measurement matrix (GRMM). Simulations indicate that the proposed measurement matrices can improve detection accuracy as compared to a GRMM

A Fair Individual Rate Comparison between MIMO-NOMA and MIMO-OMA

In this paper, we compare the individual rate of MIMO-NOMA and MIMO-OMA when users are paired into clusters. A power allocation (PA) strategy is proposed, which ensures that MIMO-NOMA achieves a higher individual rate for each user than MIMO-OMA with arbitrary PA and optimal degrees of freedom split. In addition, a special case with equal degrees of freedom and arbitrary PA for OMA is considered, for which the individual rate superiority of NOMA still holds. Moreover, it is shown that NOMA can attain better fairness through appropriate PA. Finally, simulations are carried out, which validate the developed analytical results