Abstract
For the problem of channel state information (CSI) delay and error, this paper proposes a joint interference and phase alignment algorithm based on Bayesian estimation and power allocation among data streams for multicell, multiple-input multiple-output broadcast channels (MIMO-BC). Firstly, the sender obtains the best estimate of the current CSI through Bayesian estimation. Secondly, the interference suppression matrix is designed by maximizing the ratio of the desired signal power to the intercell interference plus noise ratio (SINR) in the forward link, and in the reverse communication, by maximizing the SINR design precoding. Further, the water-filling algorithm is combined to optimize power allocation among data streams. Finally, the phase alignment is used to rotate the interference between data streams into the signal space of the target receive data stream, thereby enhancing the received power of the target data stream. Simulation results show that the proposed algorithm has certain performance advantages over other algorithms, whether it is ideal CSI or delay and error CSI.
Highlights
Multiple-input multiple-output (MIMO) is a technology which can make great enhancements in terms of the overall throughput of the network [1]
In the case of time delay error channel state information (CSI), this paper gives the solution to the existing problem by proposing a joint interference and phase alignment algorithm based on Bayesian problem by proposing a joint interference and phase alignment algorithm based on Bayesian estimation estimation and power allocation among data streams
In the case of ideal CSI and delay error CSI, the algorithm of this paper is combined with MAX-SINR-SCEK [17], minimum interference leakage (MIN-IL) [17], and the literature [11], and the system capacity, bit error rate (BER), and convergence are simulated for comparison
Summary
Multiple-input multiple-output (MIMO) is a technology which can make great enhancements in terms of the overall throughput of the network [1]. The interference scheduling algorithm is mostly based on complete and accurate channel state information (CSI). In an actual communication system, since the channel may produce errors in the estimation or measurement, the receiving end cannot completely suppress other base station interference which causes system performance loss. This paper gives the solution to the existing problem by proposing a joint interference and phase alignment algorithm based on Bayesian estimation and power allocation among data streams. The transmitter deploys Bayesian estimation to acquire the best estimate of the current CSI.
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