Cognitive broadcast channel, where two multiantenna transmitters communicate with their respective receivers, is considered. One of the transmitters is said to be cognitive (secondary) as it is assumed to know the messages of the other (primary) transmitter non-causally. The goal is to design cooperative schemes between the two transmitters, which impose only minimal changes to the primary broadcast channel (compared to the non-cognitive scenario). Towards this end, an achievable scheme is provided under which both intra cell and inter cell interferences at the primary receivers are aligned. The interference at the secondary receivers, on the other hand, is canceled by dirty paper coding. The corresponding achievable region and an outer bound region are provided in terms of the degrees of freedom (DoF) metric. Special cases shows the optimality of the proposed scheme in the high SNR regime for those cases. We also illustrate the advantage of the cognitive cooperation over the non-cognitive system by proving that the achieved sum DoF is strictly larger than the non-cognitive case.

Downlink communication in a cellular network with a cognitive (secondary) cell is considered. In our model, the base station of the cognitive cell knows the messages of the other cell non-causally. We propose a new interference cancellation technique that zero forces the intra-cell interference in the primary cell by the help of the cognitive base station. In addition, as the primary messages are known at the cognitive base station, the interference caused by the primary base station on the secondary users are canceled using dirty paper coding (DPC). Moreover, we provide an outer bound on the achievable degrees of freedom (DoF) region and show that for some special cases the proposed signaling scheme is sum DoF optimal for the considered system when the cognitive cell operates at its maximum sum DoF. The benefit of the cognitive paradigm is also established using the derived outer-bound and showing that the achieved sum DoF is strictly larger than the case when cognitive message sharing is unavailable.

We consider the discrete memoryless X channel, a communication model with two transmitters and two receivers in which every transmitter has a message for every receiver. We propose an achievable scheme, based on the message splitting and binning techniques, which results in the best inner bound on the capacity region of the X channel to date.

This paper adopts an information-theoretic framework for the design of collusion-resistant coding/decoding schemes for digital fingerprinting. More specifically, the minimum distance decision rule is used to identify 1 out oftpirates. Achievable rates, under this detection rule, are characterized in two scenarios. First, we consider the averaging attack where a random coding argument is used to show that the rate 1/2 is achievable witht=2 pirates. Our study is then extended to the general case of arbitrarythighlighting the underlying complexity-performance tradeoff. Overall, these results establish the significant performance gains offered by minimum distance decoding compared to other approaches based on orthogonal codes and correlation detectors which can support only a subexponential number of users (i.e., a zero rate). In the second scenario, we characterize the achievable rates, with minimum distance decoding, under any collusion attack that satisfies the marking assumption. Fort=2 pirates, we show that the rate 1-H(0.25) ap 0.188 is achievable using an ensemble of random linear codes. Fortges 3, the existence of a nonresolvable collusion attack, with minimum distance decoding, for any nonzero rate is established. Inspired by our theoretical analysis, we then construct coding/decoding schemes for fingerprinting based on the celebrated belief-propagation framework. Using an explicit repeat-accumulate code, we obtain a vanishingly small probability of misidentification at rate 1/3 under averaging attack witht=2. For collusion attacks, which satisfy the marking assumption, we use a more sophisticated accumulate repeat accumulate code to obtain a vanishingly small misidentification probability at rate 1/9 witht=2. These results represent a marked improvement over the best available designs in the literature.

The dual-mode CMA-assisted decision adjusted modulus algorithm (CADAMA) has been proved to be a very effective way of equalizing non-minimum phase channels blindly [Axford RA, et al., 1996]. However, it still suffers from a slow convergence when applies to the higher order QAMS. In this paper, we propose a new dual mode method for blind equalization of QAM signals, which achieves a faster convergence compared to the CADAMA. The simulation results show the better convergence rate of the proposed algorithm.