4 research outputs found

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

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    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

    Hybrid Analog-Digital Precoding for Interference Exploitation

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    We study the multi-user massive multiple-input-single-output (MISO) and focus on the downlink systems where the base station (BS) employs hybrid analog-digital precoding with low-cost 1-bit digital-to-analog converters (DACs). In this paper, we propose a hybrid downlink transmission scheme where the analog precoder is formed based on the SVD decomposition. In the digital domain, instead of designing a linear transmit precoding matrix, we directly design the transmit signals by exploiting the concept of constructive interference. The optimization problem is then formulated based on the geometry of the modulation constellations and is shown to be non-convex. We relax the above optimization and show that the relaxed optimization can be transformed into a linear programming that can be efficiently solved. Numerical results validate the superiority of the proposed scheme for the hybrid massive MIMO downlink systems.Comment: 5 pages, EUSIPCO 201

    Multi-Panel Sparse Base Station Design with Physical Antenna Effects in Massive MU-MIMO

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    A novel base station antenna (BSA) configuration is presented to mitigate degrading physical antenna effects in massive multiple-input multiple-output (MIMO) systems, while minimizing implementation complexities. Instead of using a commonly considered single antenna panel comprising of many elements covering a wide field-of-view (FOV) of 120 degrees, L tilted panels are used employing L times fewer elements and L times smaller FOV per panel. The spatial resolution of each panel is enhanced by employing sparse arrays with suppressed (grating-lobe) radiation outside its corresponding FOV. Therefore, more directive antenna elements can be deployed in each panel to compensate for the effective isotropic radiated power (EIRP) reduction. While sectorisation reduces the antenna gain variation in 120 degrees FOV, cooperation among multiple panels in downlink beamforming is seen to be capable of inter-panel interference suppression for sum-rate enhancement. A network model is used as a multi-user (MU) MIMO simulator incorporating both antenna and channel effects. It is shown that when the number of base station antennas is ten times the number of users, the average downlink sum-rate in pure line-of-sight (LOS), rich and poor multipath environments is increased up to 60.2%, 23% and 11.1%, respectively, by multi-panel sparse arrays applying zero-forcing (ZF) precoding

    Multiple-Antenna Systems: From Generic to Hardware-Informed Precoding Designs

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    5G-and-beyond communication systems are expected to be in a heterogeneous form of multiple-antenna cellular base stations (BSs) overlaid with small cells. The fully-digital BS structures can incur significant power consumption and hardware complexity. Moreover, the wireless BSs for small cells usually have strict size constraints, which incur additional hardware effects such as mutual coupling (MC). Consequently, the transmission techniques designed for future wireless communication systems should respect the hardware structures at the BSs. For this reason, in this thesis we extend generic downlink precoding to more advanced hardware-informed transmission techniques for a variety of BS structures. This thesis firstly extends the vector perturbation (VP) precoding to multiple-modulation scenarios, where existing VP-based techniques are sub-optimal. Subsequently, this thesis focuses on the downlink transmission designs for hardware effects in the form of MC, limited number of radio frequency (RF) chains, and low-precision digital-to-analog converters (DACs). For these scenarios, existing precoding techniques are either sub-optimal or not directly applicable due to the specific hardware constraints. In this context, this thesis first proposes analog-digital (AD) precoding methods for MC exploitation in compact single-user multiple-antenna systems with the concept of constructive interference, and further extends the idea of MC exploitation to multi-user scenarios with a joint optimisation on the precoding matrix and the mutual coupling effect. We further consider precoding for wireless BSs with a limited number of RF chains, in the form of compact parasitic antenna array as well as hybrid analog-digital structures designed for large-scale multiple-antenna systems. In addition, with a reformulation of the constructive interference, this thesis also considers the low-complexity precoding design for the use of low-resolution DACs for a massive-antenna array at the BSs. Analytical and numerical results reveal an improved performance of the proposed techniques compared to the state-of-the-art approaches, which validates the effectiveness of the introduced methods
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