Enhancing LTE with Cloud-RAN and Load-Controlled Parasitic Antenna Arrays

Cloud radio access network systems, consisting of remote radio heads densely distributed in a coverage area and connected by optical fibers to a cloud infrastructure with large computational capabilities, have the potential to meet the ambitious objectives of next generation mobile networks. Actual implementations of C-RANs tackle fundamental technical and economic challenges. In this article, we present an end-to-end solution for practically implementable C-RANs by providing innovative solutions to key issues such as the design of cost-effective hardware and power-effective signals for RRHs, efficient design and distribution of data and control traffic for coordinated communications, and conception of a flexible and elastic architecture supporting dynamic allocation of both the densely distributed RRHs and the centralized processing resources in the cloud to create virtual base stations. More specifically, we propose a novel antenna array architecture called load-controlled parasitic antenna array (LCPAA) where multiple antennas are fed by a single RF chain. Energy- and spectral-efficient modulation as well as signaling schemes that are easy to implement are also provided. Additionally, the design presented for the fronthaul enables flexibility and elasticity in resource allocation to support BS virtualization. A layered design of information control for the proposed end-to-end solution is presented. The feasibility and effectiveness of such an LCPAA-enabled C-RAN system setup has been validated through an over-the-air demonstration

Tunable Load MIMO with Quantized Loads

In this paper, we study the application of precoding schemes on practical electronically steerable parasitic array radiators (ESPARs), where quantized load impedances are considered for each antenna element. The presence of quantization in the loads results in a performance loss for practical ESPARs. To alleviate the performance loss, we propose to approximate the ideal current vector with convex optimization, where it is further shown that the optimality is achieved by optimizing the feeding voltages only. Specifically, we obtain the closed-form expression when single-fed ESPARs are assumed. Numerical results show that the proposed quantization-robust scheme can achieve a significant performance gain over ESPARs with quantized loads

Exploiting Constructive Mutual Coupling in P2P MIMO by Analog-Digital Phase Alignment

In this paper, we propose a joint analog-digital (A/D) beamforming scheme for the point-to-point multiple-input-multiple-output system, where we exploit mutual coupling by optimizing the load impedances of the transmit antennas. Contrary to the common conception that mutual coupling strictly harms the system performance, we show that mutual coupling can be beneficial by exploiting the concept of constructive interference. By changing the value of each load impedance for the antenna array based on convex optimization, the mutual coupling effect can be manipulated so that the resulting interference aligns constructively to the useful signal vector. We first prove that the full elimination of mutual coupling effect is not achievable solely by tuning the values of the antenna load impedances. We then introduce the proposed A/D scheme for both PSK and QAM modulations, where performance gains with respect to conventional techniques are obtained. The implementation of the proposed schemes is also discussed, where a lookup table can be built to efficiently apply the calculated load impedances. The numerical results show that the proposed schemes can achieve an improved performance compared to systems with fixed mutual coupling, especially when the antenna spacing is small

MIMO Transmission for Single-fed ESPAR with Quantized Loads

Compact parasitic arrays in the form of electronically steerable parasitic antenna radiators (ESPARs) have emerged as a new antenna structure that achieves multipleinput- multiple-output (MIMO) transmission with a single RF chain. In this paper, we study the application of precoding on practical ESPARs, where the antennas are equipped with load impedances of quantized values. We analytically study the impact of the quantization on the system performance, where it is shown that while ideal ESPARs with ideal loads can achieve a similar performance to conventional MIMO, the performance of ESPARs will be degraded when only loads with quantized values are available. We further extend the performance analysis to imperfect channel state information (CSI). In order to alleviate the performance loss, we propose to approximate the ideal current vector by optimization, where a closed-form solution is further obtained. This enables the use of ESPARs in practice with quantized loads. Simulation results validate our analysis and show that a significant performance gain can be achieved with the proposed scheme over ESPARs with quantized loads. Finally, the tradeoff between performance and power consumption is shown to be favorable for the proposed ESPAR approaches compared to conventional MIMO, as evidenced by our energy efficiency results

Analog-Digital Beamforming in the MU-MISO Downlink by use of Tunable Antenna Loads

We investigate the performance of multi-user multiple-input-single-output (MU-MISO) downlink in the presence of the mutual coupling effect at the transmitter. Contrary to traditional approaches that aim at eliminating this effect, in this paper we propose a joint analog-digital (AD) beamforming scheme that exploits this effect to further improve the system performance. A jointly optimal AD beamformer is firstly obtained by iteratively maximizing the minimum received signal-to-interference-plus-noise ratio (SINR) in the digital domain, followed by an optimization on the load impedance of each antenna element in the analog domain. We further introduce a decoupled low-complexity approach, with which existing closed-form beamforming schemes can also be efficiently applied. For the consideration of hardware imperfections in practice, we study the case where the analog load values are quantized, and propose a sequential search scheme based on greedy algorithm to efficiently obtain the desired quantized load values. Moreover, we also investigate the imperfect channel state information (CSI) scenarios, where we prove the optimality for closed-form beamformers, and further propose the robust schemes for two typical CSI error models. Simulation results show that with the proposed schemes the mutual coupling effect can be exploited to further improve the performance for both perfect CSI and imperfect CSI