Deployment Strategies of Multiple Aerial BSs for User Coverage and Power Efficiency Maximization

Unmanned aerial vehicle (UAV) based aerial base stations (BSs) can provide rapid communication services to ground users and are thus promising for future communication systems. In this paper, we consider a scenario where no functional terrestrial BSs are available and the aim is deploying multiple aerial BSs to cover a maximum number of users within a certain target area. To this end, we first propose a naive successive deployment method, which converts the non-convex constraints in the involved optimization into a combination of linear constraints through geometrical relaxation. Then we investigate a deployment method based on K-means clustering. The method divides the target area into K convex subareas, where within each subarea, a mixed integer non-linear problem (MINLP) is solved. An iterative power efficient technique is further proposed to improve coverage probability with reduced power. Finally, we propose a robust technique for compensating the loss of coverage probability in the existence of inaccurate user location information (ULI). Our simulation results show that, the proposed techniques achieve an up to 30% higher coverage probability when users are not distributed uniformly. In addition, the proposed simultaneous deployment techniques, especially the one using iterative algorithm improve power-efficiency by up to 15% compared to the benchmark circle packing theory

Hybrid Beamforming With Sub-arrayed MIMO Radar: Enabling Joint Sensing and Communication at mmWave Band

In this paper, we propose a beamforming design for dual-functional radar-communication (DFRC) systems at the millimeter wave (mmWave) band, where hybrid beamforming and sub-arrayed MIMO radar techniques are jointly exploited. We assume that a base station (BS) is serving a user equipment (UE) located in a Non-Line-of-Sight (NLoS) channel, which in the meantime actively detects multiple targets located in a Line-of-Sight (LoS) channel. Given the optimal communication beamformer and the desired radar beampattern, we propose to design the analog and digital beamformers under non-convex constant-modulus (CM) and power constraints, such that the weighted summation of the communication and radar beamforming errors is minimized. The formulated optimization problem can be decomposed into three subproblems, and is solved by the alternating minimization approach. Numerical simulations verify the feasibility of the proposed beamforming design, and show that our approach offers a favorable performance tradeoff between sensing and communication.Comment: 5 pages, 2 figures, submitted to ICASSP 201

Hybrid Analog-Digital Precoding for Interference Exploitation

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

Interference Exploitation-based Hybrid Precoding with Robustness Against Phase Errors

Hybrid analog-digital precoding significantly reduces the hardware costs in massive MIMO transceivers when compared to fully-digital precoding at the expense of increased transmit power. In order to mitigate the above shortfall, we use the concept of constructive interference-based precoding, which has been shown to offer significant transmit power savings when compared with the conventional interference suppression-based precoding in fully-digital multiuser MIMO systems. Moreover, in order to circumvent the potential quality-of-service degradation at the users due to the hardware impairments in the transmitters, we judiciously incorporate robustness against such vulnerabilities in the precoder design. Since the undertaken constructive interference-based robust hybrid precoding problem is nonconvex with infinite constraints and thus difficult to solve optimally, we decompose the problem into two subtasks, namely, analog precoding and digital precoding. In this paper, we propose an algorithm to compute the optimal constructive interference-based robust digital precoders. Furthermore, we devise a scheme to facilitate the implementation of the proposed algorithm in a low-complexity and distributed manner. We also discuss block-level analog precoding techniques. Simulation results demonstrate the superiority of the proposed algorithm and its implementation scheme over the state-of-the-art methods

Reduced Switching Connectivity for Large Scale Antenna Selection

In this paper, we explore reduced-connectivity radio frequency (RF) switching networks for reducing the analog hardware complexity and switching power losses in antenna selection (AS) systems. In particular, we analyze different hardware architectures for implementing the RF switching matrices required in AS designs with a reduced number of RF chains. We explicitly show that fully-flexible switching matrices, which facilitate the selection of any possible subset of antennas and attain the maximum theoretical sum rates of AS, present numerous drawbacks such as the introduction of significant insertion losses, particularly pronounced in massive multiple-input multiple-output (MIMO) systems. Since these disadvantages make fully-flexible switching suboptimal in the energy efficiency sense, we further consider partially-connected switching networks as an alternative switching architecture with reduced hardware complexity, which we characterize in this work. In this context, we also analyze the impact of reduced switching connectivity on the analog hardware and digital signal processing of AS schemes that rely on channel power information. Overall, the analytical and simulation results shown in this paper demonstrate that partially-connected switching maximizes the energy efficiency of massive MIMO systems for a reduced number of RF chains, while fully-flexible switching offers sub-optimal energy efficiency benefits due to its significant switching power losses.Comment: 14 pages, 11 figure

1-Bit Massive MIMO Downlink Based on Constructive Interference

In this paper, we focus on the multiuser massive multiple-input single-output (MISO) downlink with low-cost 1-bit digital-to-analog converters (DACs) for PSK modulation, and propose a low-complexity refinement process that is applicable to any existing 1-bit precoding approaches based on the constructive interference (CI) formulation. With the decomposition of the signals along the detection thresholds, we first formulate a simple symbol-scaling method as the performance metric. The low-complexity refinement approach is subsequently introduced, where we aim to improve the introduced symbol-scaling performance metric by modifying the transmit signal on one antenna at a time. Numerical results validate the effectiveness of the proposed refinement method on existing approaches for massive MIMO with 1-bit DACs, and the performance improvements are most significant for the low-complexity quantized zero-forcing (ZF) method.Comment: 5 pages, EUSIPCO 201

Sum Rate and Fairness Analysis for the MU-MIMO Downlink under PSK Signalling: Interference Suppression vs Exploitation

In this paper, we analyze the sum rate performance of multi-user multiple-input multiple-output (MU-MIMO) systems, with a finite constellation phase-shift keying (PSK) input alphabet. We analytically calculate and compare the achievable sum rate in three downlink transmission scenarios: 1) without precoding, 2) with zero forcing (ZF) precoding 3) with closed form constructive interference (CI) precoding technique. In light of this, new analytical expressions for the average sum rate are derived in the three cases, and Monte Carlo simulations are provided throughout to validate the analysis. Furthermore, based on the derived expressions, a power allocation scheme that can ensure fairness among the users is also proposed. The results in this work demonstrate that, the CI strictly outperforms the other two schemes, and the performance gap between the considered schemes increases with increase in the MIMO size. In addition, the CI provides higher fairness and the power allocation algorithm proposed in this paper can achieve maximum fairness index

Space-Constrained Massive MIMO: Hitting the Wall of Favorable Propagation

The recent development of the massive multiple-input multiple-output (MIMO) paradigm, has been extensively based on the pursuit of favorable propagation: in the asymptotic limit, the channel vectors become nearly orthogonal and inter-user interference tends to zero [1]. In this context, previous studies have considered fixed inter-antenna distance, which implies an increasing array aperture as the number of elements increases. Here, we focus on a practical, space-constrained topology, where an increase in the number of antenna elements in a fixed total space imposes an inversely proportional decrease in the inter-antenna distance. Our analysis shows that, contrary to existing studies, inter-user interference does not vanish in the massive MIMO regime, thereby creating a saturation effect on the achievable rate