On Secrecy Capacity of Fast Fading MIMOME Wiretap Channels With Statistical CSIT

In this paper, we consider secure transmissions in ergodic Rayleigh fast-faded multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) wiretap channels with only statistical channel state information at the transmitter (CSIT). When the legitimate receiver has more (or equal) antennas than the eavesdropper, we prove the first MIMOME secrecy capacity with partial CSIT by establishing a new secrecy capacity upper-bound. The key step is to form an MIMOME degraded channel by dividing the legitimate receiver's channel matrix into two submatrices, and setting one of the submatrices to be the same as the eavesdropper's channel matrix. Next, under the total power constraint over all transmit antennas, we analytically solve the channel-input covariance matrix optimization problem to fully characterize the MIMOME secrecy capacity. Typically, the MIMOME optimization problems are non-concave. However, thank to the proposed degraded channel, we can transform the stochastic MIMOME optimization problem to be a Schur-concave one and then find its solution. Besides total power constraint, we also investigate the secrecy capacity when the transmitter is subject to the practical per-antenna power constraint. The corresponding optimization problem is even more difficult since it is not Schuar-concave. Under the two power constraints considered, the corresponding MIMOME secrecy capacities can both scale with the signal-to-noise ratios (SNR) when the difference between numbers of antennas at legitimate receiver and eavesdropper are large enough. However, when the legitimate receiver and eavesdropper have a single antenna each, such SNR scalings do not exist for both cases.Comment: submitted to IEEE Transactions on Wireless Communication

B to V, A, T Tensor Form Factors in the Covariant Light-Front Approach: Implications on Radiative B Decays

We reanalyze the $B\to M$ tensor form factors in a covariant light-front quark model, where $M$ represents a vector meson $V$, an axial-vector meson $A$, or a tensor meson $T$. The treatment of masses and mixing angles in the $K_{1A,1B}$ systems is improved, where $K_{1A}$ and $K_{1B}$ are the $^3P_1$ and $^1P_1$ states of the axial-vector meson $K_1$, respectively. Rates of $B\to M\gamma$ decays are then calculated using the QCD factorization approach. The updated $B\to K^*\gamma$, $B\to K_1(1270)\gamma$, $K_1(1400)\gamma$ and $K_2\gamma$ rates agree with the data. The $K_1(1270)$--$K_1(1400)$ mixing angle is found to be about $51^\circ$. The sign of the mixing angle is fixed by the observed relative strength of $B\to K_1(1270)\gamma$ and $K_1(1400)\gamma$. The formalism is then applied to $B_s\to M$ tensor form factors. We find that the calculated $B_s\to \phi\gamma$ rate is consistent with experiment, though in the lower end of the data. The branching fractions of $B_s\to f_1(1420)\gamma$ and $f'_2(1525)\gamma$ are predicted to be of order $10^{-5}$ and it will be interesting to search for these modes. Rates on $B_s\to f_1(1285)\gamma$, $h_1(1380)\gamma$, $h_1(1170)\gamma$, $f_2(1270)\gamma$ decays are also predicted.Comment: 26 pages, 3 figures, version to appear in PR

Robust And Optimal Opportunistic Scheduling For Downlink 2-Flow Network Coding With Varying Channel Quality and Rate Adaptation

This paper considers the downlink traffic from a base station to two different clients. When assuming infinite backlog, it is known that inter-session network coding (INC) can significantly increase the throughput of each flow. However, the corresponding scheduling solution (when assuming dynamic arrivals instead and requiring bounded delay) is still nascent. For the 2-flow downlink scenario, we propose the first opportunistic INC + scheduling solution that is provably optimal for time-varying channels, i.e., the corresponding stability region matches the optimal Shannon capacity. Specifically, we first introduce a new binary INC operation, which is distinctly different from the traditional wisdom of XORing two overheard packets. We then develop a queue-length-based scheduling scheme, which, with the help of the new INC operation, can robustly and optimally adapt to time-varying channel quality. We then show that the proposed algorithm can be easily extended for rate adaptation and it again robustly achieves the optimal throughput. A byproduct of our results is a scheduling scheme for stochastic processing networks (SPNs) with random departure, which relaxes the assumption of deterministic departure in the existing results. The new SPN scheduler could thus further broaden the applications of SPN scheduling to other real-world scenarios