In multi-hop relay systems, the end-to-end channel capacity is restricted by bottleneck node. In order to prevent some relay nodes from being the bottleneck of system and to guarantee the end-to-end channel capacity, the method of optimizing transmit power, distance and allocation time is proposed in this article. We show that the optimizing distance has more end-to-end channel capacity than the optimizing transmit power in case that both the distance and the transmit power are changeable. However, the optimizing transmit power can let the system reach high end-to-end channel capacity when the relay nodes have to shift from the desired location. We also propose the Markov Chain Monte Carlo method to optimize all transmit power, distance and allocation time simultaneously. The optimizing all transmit power, distance and allocation time is the most effective and achieves the highest channel capacity. Based on the average signal-to-noise-ratio, the average channel capacity is evaluated in this article.
In multiple users (MU) multiple input multiple output (MIMO) systems, the non-orthogonal multiple access (NOMA) method can provide multiple access. However, a spectrum efficiency of NOMA method is restricted because of remaining an interference signal of another user. A beamforming method can also be applied into MU-MIMO systems for implementation of multiple access without the interference with the other users; however, it is unavailable for a high density user environment in which multiple users locate close to each other. In order to further improve the spectrum efficiency, we propose a novel signal processing method which joints a precoding and an equalization. First, a precoding matrix is prepared for every user at base station, and we design an equalization which is orthogonal to the precoding matrix. Second, a set of linear weights is proposed to calculate at users for cancelling any interference signal. Therefore, signals for other users are eliminated according to the orthogonal feature and linear signal processing, and then, every user can receive its own signal without the interference signal. The proposed method is compared with the beamforming and NOMA methods in several scenarios, and the calculation result shows that our method outperforms other methods. Especially, our novel method works properly in the case of high density users.
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