Wireless Communication with Cross-Linked Rotatable Antenna Array: Architecture Design and Rotation Optimization
🤖 AI Summary
This work proposes a cross-linked (CL) rotatable antenna array architecture to address the scalability limitations of conventional rotatable antenna systems, whose hardware cost and control complexity grow linearly with the number of antennas. By jointly coordinating the three-dimensional orientations of multiple antennas, the CL architecture enhances spatial degrees of freedom while reducing hardware overhead. Two novel rotation schemes—element-level and panel-level—are introduced, and a joint optimization framework is developed to co-design base station receive beamforming and discrete rotation angles, solved via alternating optimization, MMSE beamforming, and a genetic algorithm. Simulations demonstrate that, under appropriate row–column grouping, the CL architecture achieves performance close to that of a fully flexible system; notably, the element-level scheme outperforms the panel-level counterpart by 25% and surpasses traditional fixed-antenna arrays by 128%.
Application Category
📝 Abstract
Rotatable antenna (RA) technology can harness additional spatial degrees of freedom by enabling the dynamic three-dimensional orientation control of each antenna. Unfortunately, the hardware cost and control complexity of traditional RA systems is proportional to the number of RAs. To address the issue, we consider a cross-linked (CL) RA structure, which enables the coordinated rotation of multiple antennas, thereby offering a cost-effective solution. To evaluate the performance of the CL-RA array, we investigate a CL-RA-aided uplink system. Specifically, we first establish system models for both antenna element-level and antenna panel-level rotation. Then, we formulate a sum rate maximization problem by jointly optimizing the receive beamforming at the base station and the rotation angles. For the antenna element-level rotation, we derive the optimal solution of the CL-RA array under the single-user case. Subsequently, for two rotation schemes, we propose an alternating optimization algorithm to solve the formulated problem in the multi-user case, where the receive beamforming and the antenna rotation angles are obtained by applying the minimum mean square error method and feasible direction method, respectively. In addition, considering the hardware limitations, we apply the genetic algorithm to address the discrete rotation angles selection problem. Simulation results show that by carefully designing the row-column partition scheme, the performance of the CL-RA architecture is quite close to that of the flexible antenna orientation scheme. Moreover, the CL antenna element-level scheme surpasses the CL antenna panel-level scheme by 25% and delivers a 128% performance improvement over conventional fixed-direction antennas.
Problem
Research questions and friction points this paper is trying to address.
Rotatable Antenna
Hardware Cost
Control Complexity
Spatial Degrees of Freedom
Antenna Array
Innovation
Methods, ideas, or system contributions that make the work stand out.
Cross-Linked Rotatable Antenna
Spatial Degrees of Freedom
Alternating Optimization
Genetic Algorithm
Sum Rate Maximization
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