Abstract
The highly sparse nature of propagation channels and the restricted use of radio frequency (RF) chains at transceivers limit the performance of millimeter wave (mmWave) multiple-input multiple- output (MIMO) systems. Introducing reconfigurable antennas to mmWave can offer an additional degree of freedom on designing mmWave MIMO systems. This paper provides a theoretical framework for studying the mmWave MIMO with reconfigurable antennas. We present an architecture of reconfigurable mmWave MIMO with beamspace hybrid analog-digital beamformers and reconfigurable antennas at both the transmitter and the receiver. We show that employing reconfigurable antennas can provide throughput gain for the mmWave MIMO. We derive the expression for the average throughput gain of using reconfigurable antennas, and further simplify the expression by considering the case of large number of reconfiguration states. In addition, we propose a low-complexity algorithm for the reconfiguration state and beam selection, which achieves nearly the same throughput performance as the optimal selection of reconfiguration state and beams by exhaustive search.
Highlights
The ubiquitous use of wireless devices in modern life is creating a capacity crisis in wireless communications
We assume that θψr,i,l are uniformly distributed with mean θψr,i and a constant angular spread σθr . θψt,i,l are uniformly distributed with mean θψt,i and a constant angular spread σθt
We have presented a framework for the theoretical study of the millimeter wave (mmWave) multiple-input multiple-output (MIMO) with reconfigurable antennas, where the low-complexity transceivers and the sparse channels are considered
Summary
The ubiquitous use of wireless devices in modern life is creating a capacity crisis in wireless communications. The high cost and power consumption of RF components and data converters preclude the adoption of fully digital processing for mmWave MIMO to achieve large beamforming gains [1], [4], and low-complexity transceivers relying heavily on analog or hybrid (analog-digital) processing are often adopted [5]–[7]. Due to the simple structure of a 2×2 MIMO, neither the important sparse nature of mmWave channels nor the transceivers with low-complexity beamforming were considered in [18] and [19]. We take the sparse nature of mmWave channels into account, and present a practical architecture of the mmWave MIMO with low-complexity beamformers and reconfigurable antennas. Taking advantage of the sparse nature of mmWave channels, the proposed algorithm significantly reduces the complexity of the reconfiguration state and beam selection, and achieves nearly the same throughput performance as the optimal selection of reconfiguration state and beams by exhaustive search. Notations: XT and XH denote the transpose and conjugate transpose of X, respectively, X (m, n) denotes the entry of X in the m-th row and n-th column, Tr(X) denotes the trace of X, |X| denotes the determinant of X, X F denotes the Frobenius norm of X, Re[x] and Im[x] denote the real and imaginary parts of x, respectively, ⊙ denotes the Hadamard (element-wise) product, |X | denotes the cardinality of set X , sgn(·) denotes the sign function, erf(·) denotes the error function, erf−1(·) denotes the inverse error function, E{·} denotes the expectation operation, P(·) denotes the probability measure, In denotes the identity matrix of size n, CN (μ, σ2) denotes the complex Gaussian distribution with mean μ and variance σ2, and CN (a, A) denotes the distribution of a circularly symmetric complex Gaussian random vector with mean a and covariance matrix A
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
