Interference alignment method for minimizing interference power and dimension

Abstract

The invention discloses an interference alignment method for minimizing interference power and dimension. The method comprises the steps: 1, randomly generating an interference inhibition matrix, and setting an iteration number iter; 2, taking the nuclear norm of an interference mapping matrix as a target function, letting a desired signal matrix be a Hermitian positive definite matrix, and taking a condition that a minimum characteristic value is greater than or equal to 100 as a constraint condition, and solving a pre-coding matrix; 3, taking a received interference signal as the whole body, and solving an interference covariance matrix; 4, letting a characteristic vector corresponding to the minimum characteristic value of the interference covariance matrix be a column vector of the interference inhibition matrix; 5, judging whether all iterations are completed or not: carrying out the orthogonalization of the pre-coding matrix and the interference inhibition matrix if all iterations are completed, or else, returning to step 2. The method can improve the quality of received signals, enlarges the system capacity, and improves the utilization rate of frequency spectrum.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to an interference alignment method for minimizing interference power and dimension. Background technique [0002] Multiple-antenna technology (Multiple Input Multiple Output, MIMO), because it can significantly improve the throughput of the wireless communication system, has attracted extensive attention. This technology introduces an additional degree of freedom into the communication system by configuring multiple antennas at the transmitting end and receiving end, and improves channel capacity and spectrum utilization without increasing bandwidth and antenna transmission power. Although multi-antenna technology has opened up airspace resources, improved communication quality, and increased the channel capacity of wireless communication systems, fading and interference have always been two major obstacles in information dissemination. When a signal pro...

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Problems solved by technology

DimitrisS.Papailiopoulos and AlexandrosG.Dimakis published "InterferenceAlignmentasaRankConstrainedRankMinimization" in IEEETransactionsonSignalProcessing, 2012, using the characteristic that the matrix kernel norm is the convex envelope of rank to propose a rank-constrained rank minimization algorithm (RCRM). Although it solves the problem of non-convex objective function, The degree of freedom of the user is improved, but the algorithm only limits the dimension of the interference signal. If the leaked interference power is large, the system still cannot obtain a high capacity

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