| All kinds of interferences are the major impairments to successful communication incivil and military wireless systems. In cellular systems, interference is created whendifferent base stations share the same carrier frequency due to frequency reuse. Inter cellinterference reduces data rates throughout the cells and causes outages at the cell edges. Inlocal area networks, interference is created when different access points share the samechannel. The medium access control (MAC) protocol attempts to deal with interference byavoiding packet collisions. This conservative approach leads to under-utilization of systembandwidth. The medium access control protocol again limits the number of simultaneousconversations and consequently the system performance. How to implementcommunication without interference in some sense is thus becoming a hot problem in mostwireless systems.In recent years, a new way for implementing communication without interference ininterference channels, called interference alignment (IA), which was proposed and gotmore and more attention. In fact, IA is a cooperative interference management strategy thatexploits the availability of multiple signaling dimensions provided by multiple time slots,frequency blocks, or antennas. The transmitters jointly design their transmitted signals inthe multidimensional space such that the interference observed at the receivers occupiesonly a portion of the full signaling space, and the desired signals are in a non-interferencesubspace.Interference alignment in its simplest form is a precoding technique for theinterference channel. It is a transmission strategy that linearly encodes signals overmultiple dimensions. IA solves the problem that the spectrum efficiency of each userdecreases as the user number increases, and it increases the sum-capacity. But, interferencealignment relies on some special assumptions that must be relaxed before it is adopted inpractical wireless systems. This paper is supported under the MIMO channel, focusing onthe great application potential of interference alignment technology in wirelesscommunication network.In this paper, we describes the basic idea of interference alignment, and we analysisthe current trends of this technology in development, and summarizes some typicalinterference alignment algorithms’ implementations for multi-user MIMO interferencealignment under research status algorithms exist. We propose a new blind interferencealignment algorithm which combines the blind source separation model and interferencealignment model to solve the case of transmitters and receivers without the perfect channelstate information. While optimizing the system performance, we realize the separation of both the interference signals and the desired signals. Through digital simulation experimentby the computer, the simulation performance of the existing algorithms are analyzed andcompared.Most algorithms on blind interference alignment (BIA) uses non-statisticalequivalence between users based on assuming constant channel in adjacent time andfrequency slot, through adjusting antenna characteristics and changing channel correlationblock mode in order to achieve blind interference alignment. But, the complexity ofalgorithms for multi-antenna transmission of this method is extremely high for theirrealization. This paper presents a new IA algorithm with blind source separation for K userMIMO interference channel on the basis of already built interference alignment (IA)design at transmitters. The desired signal is extracted by FastICA（Fast IndependentComponents Analysis） method at receivers. Our goal is to get the illustrate BERperformance close to the IA method with full-CSI.The simulation results show that the proposed scheme breaks the limitation of thecondition of perfect channel state information at receivers, excludes its impact on systemperformance. It significantly achieves good system performance of BER, and it provides anew innovative thinking in blind interference alignment of multi-users MIMOcommunication system. |
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