Joint Interference Alignment and Power Allocation for K-User Multicell MIMO Channel through Staggered Antenna Switching

Abstract

In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K-user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K-user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K-user multicell MIMO scheduling and K-user L-cell CEUs partial cooperation algorithms elaborate the generalisation of K-user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes.

A Novel Codeword Selection Scheme for MIMO-MAC Lower-Bound Maximization

“…When the system is configured as and , the corresponding system SEs are shown in Figure 11 and Figure 12 , respectively, and they are compared with [ 39 , 40 ] for performance evaluation. It is assumed that there is no power loss when the signal propagates to the BS.…”

“…It is assumed that there is no power loss when the signal propagates to the BS. As can be seen in Figure 11 , under the configuration of , each user has a DoF of 1 (i.e., a single data stream), and [ 39 , 40 ] have the same performance by completely, eliminating the interference algorithm, but the performance is the same. The scheme cannot guarantee the compression of the interference rotation to the optimal receiving direction, and the algorithm in this paper gradually improves the performance by gradually, iteratively rotating and compressing the interference to facilitate the signal receiving direction.…”

“…In the configuration of , the DoF of each user is 2, and [ 39 ] considers the correlation between user data streams when designing the precoding matrix. Its performance is better than that of [ 40 ].…”

“…Its performance is better than that of [ 40 ]. The proposed iterative design of the interference suppression matrix gradually rotates the compression interference, and its performance is better than that of both [ 39 , 40 ].…”

“…Because [ 40 ] uses the scheme quantizing the channel matrix, its performance is worse than that of [ 39 ] due to its large quantization error. In addition, it can also be seen that: In the case of multiple degrees of freedom, the performance of the proposed algorithm is improved relative to the [ 12 , 14 , 39 , 40 ]. The bit allocation scheme of this paper improves the spectrum utilization of the algorithm when the feedback is limited.…”