Infinite Number Of Antennas Research Articles

Performance Analysis of Active Large Intelligent Surfaces (LISs): Uplink Spectral Efficiency and Pilot Training

Large intelligent surfaces (LISs) constitute a new and promising wireless communication paradigm that relies on the integration of a massive number of antenna elements over the entire surfaces of man-made structures. The LIS concept provides many advantages, such as the capability to provide reliable and space-intensive communications by effectively establishing line-of-sight (LOS) channels. In this paper, the system spectral efficiency (SSE) of an active LIS system is asymptotically analyzed under a practical LIS environment with a well-defined uplink frame structure. In order to verify the impact on the SSE of pilot contamination, the SSE of a multi-LIS system is asymptotically studied and a theoretical bound on its performance is derived. Given this performance bound, an optimal pilot training length for multi-LIS systems subjected to pilot contamination is characterized and, subsequently, the number of devices that need to be serviced by the LIS in order to maximize the performance is derived. Simulation results show that the derived analyses are in close agreement with the exact mutual information in presence of a large number of antennas, and the achievable SSE is limited by the effect of pilot contamination and intra/inter-LIS interference through the LOS path, even if the LIS is equipped with an infinite number of antennas. Additionally, the SSE obtained with the proposed pilot training length and number of scheduled devices is shown to reach the one obtained via a brute-force search for the optimal solution.

Channel Shortening by Large Multiantenna Precoding in OFDM

A channel delay spread larger than the cyclic prefix (CP) creates inter-carrier/symbol interference (ISI/ICI) in orthogonal frequency-division multiplexing (OFDM). Recent interests in low-latency applications have motivated the usage of shorter OFDM symbols where one can either downscale the CP at the cost of interference, or maintain it but with larger overhead. Alternatively, this paper studies channel shortening methods exploiting the properties of large multi-antenna precoding in order to steer the transmitted signal energy toward channel paths inside an insufficient CP. It is shown that ISI/ICI can asymptotically be canceled by conventional subcarrier-based precoding with an infinite number of antennas. This is achieved by introducing time-delay selectivity inside frequency-selective precoders in order to remove undesired delayed signals, providing a trade-off between interference mitigation and multi-path combining gains, and leading to subsequent gains in high SNR. This frequency-domain precoding method, coined time-frequency (TF) precoding, is compared to time-reversal (TR) filtering whose asymptotic rate is optimal but introduces post-modulation processing with channel-dependent signal distortion. In addition to maintain the legacy precoded multi-antenna OFDM structure, finite-size analysis shows that TF-precoding converges faster to its asymptotic rate than TR-filtering, so that TF-precoding can outperform TR-filtering in the high-SNR regime with not-so-many antennas.

On the Pilot Contamination Attack in Multi-Cell Multiuser Massive MIMO Networks

In this paper, we analyze pilot contamination (PC) attacks on a multi-cell massive multiple-input multiple-output (MIMO) network with correlated pilots. We obtain correlated pilots using a user capacity-achieving pilot sequence design. This design relies on an algorithm which designs correlated pilot sequences based on signal-to-interference-plus-noise ratio (SINR) requirements for all the legitimate users. The pilot design is capable of achieving the SINR requirements for all users even in the presence of PC. However, this design has some intrinsic limitations and vulnerabilities, such as a known pilot sequence and the non-zero cross-correlation among different pilot sequences. We reveal that such vulnerabilities may be exploited by an active attacker to increase PC in the network. Motivated by this, we analyze the correlated pilot design for vulnerabilities that can be exploited by an active attacker. Based on this analysis, we develop an effective active attack strategy in the massive MIMO network with correlated pilot sequences. Our examinations reveal that the user capacity region of the network is significantly reduced in the presence of the active attack. Importantly, the SINR requirements for the worst-affected users may not be satisfied even with an infinite number of antennas at the base station.

Massive MIMO Radar for Target Detection

Since the seminal paper by Marzetta from 2010, the Massive MIMO paradigm in communication systems has changed from being a theoretical scaled-up version of MIMO, with an infinite number of antennas, to a practical technology. Its key concepts have been adopted in the 5G new radio standard and base stations, where 64 fully-digital transceivers have been commercially deployed. Motivated by these recent developments, this paper considers a co-located MIMO radar with M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> transmitting and M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> receiving antennas and explores the potential benefits of having a large number of virtual spatial antenna channels N = M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> . Particularly, we focus on the target detection problem and develop a robust Wald-type test that guarantees certain detection performance, regardless of the unknown statistical characterization of the disturbance. Closed-form expressions for the probabilities of false alarm and detection are derived for the asymptotic regime N → ∞. Numerical results are used to validate the asymptotic analysis in the finite system regime with different disturbance models. Our results imply that there always exists a sufficient number of antennas for which the performance requirements are satisfied, without any a-priori knowledge of the disturbance statistics. This is referred to as the Massive MIMO regime of the radar system.

Optimal Precoding in the Relay and the Optimality of Largest Eigenmode Relaying with Statistical Channel State Information

An optimal precoding method for a multiple antenna relay node is investigated in order to maximize the achievable rate of the cooperative communication system. It is assumed that only the channel covariance matrices of the relay's receive and transmit channels are available to the relay and that the antennas of the relay are correlated. It is shown that the optimal transmission from the relay should be conducted in the direction of the eigenvectors of the channel covariance matrix. Moreover, necessary and sufficient conditions are derived under which the relay transmission achieves capacity by transmitting from the strongest eigenvector only; this method is called Largest Eigenmode Relaying (LER). The exact result contains an expectation operation that needs to be solved numerically; to reduce the computational complexity, novel methods are proposed that lead to closed-form solutions. A lower bound for the optimal region of LER is derived. Moreover, the effect of the number of source antennas on the optimality of LER is investigated asymptotically. The simulation results show very little difference between the regions in which LER is optimal when the source is equipped with a finite or an infinite number of antennas.