Optimized transmission for multiple input multiple output interference channel with additive white Gaussian noise

Multiple input multiple output (MIMO) systems have been shown to have tremendous potential in increasing the average throughput in cellular wireless communication systems. Improve the achievable rates of Gaussian MIMO interference channels (ICs) with additive white Gaussian noise (AWGN), when improper or circularly asymmetric complex Gaussian signaling is applied. For the MIMO-IC, the interference treated as Gaussian noise, show that the user's achievable rate can be expressed as a summation of the rate achievable by the conventional proper or circularly symmetric complex Gaussian signaling in terms of the users' transmit covariance matrices, and an additional term, which is a function of both the users' transmit covariance and pseudo-covariance matrices. The additional degrees of freedom in the pseudo-covariance matrix, which is conventionally set to be zero for the case of proper Gaussian signaling, provide an opportunity to further improve the achievable rates of Gaussian MIMO-ICs by employing improper Gaussian signaling. Propose an algorithm to design optimal transmission for k users with channel state information. Then maximize the Weighted sum rate(WSR) of MIMO Interference channels to provide Minimum Weighted Sum Mean Squared Error (MWSMSE). And proposes widely linear precoding, which efficiently maps proper information-bearing signals to improper transmitted signals at each transmitter. Joint and separate covariance, pseudo-covariance optimization algorithm is also proposed. Which guarantees the rate improvement over conventional proper Gaussian signaling.