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Register a new userSingle-Carrier Modulation for Large-Scale Antenna Systems
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Added by
Yinsheng Liu
Publication date
2015
fields
Informatics Engineering
and research's language is
English
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Large-scale antenna (LSA) has gained a lot of attention due to its great potential to significantly improve system throughput. In most existing works on LSA systems, orthogonal frequency division multiplexing (OFDM) is presumed to deal with frequency selectivity of wireless channels. Although LSA-OFDM is a natural evolution from multiple-input multiple-output OFDM (MIMO-OFDM), the drawbacks of LSA-OFDM are inevitable, especially when used for the uplink. In this paper, we investigate single-carrier (SC) modulation for the uplink transmission in LSA systems based on a novel waveform recovery theory, where the receiver is designed to recover the transmit waveform while the information-bearing symbols can be recovered by directly sampling the recovered waveform. The waveform recovery adopts the assumption that the antenna number is infinite and the channels at different antennas are independent. In practical environments, however, the antenna number is always finite and the channels at different antennas are also correlated when placing hundreds of antennas in a small area. Therefore, we will also analyze the impacts of such non-ideal environments.
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Large-scale antenna (LSA) or massive multiple-input multiple-output (MIMO) has gained a lot of attention due to its potential to significantly improve system throughput. As a natural evolution from traditional MIMO-orthogonal frequency division multiplexing (OFDM), LSA has been combined with OFDM to deal with frequency selectivity of wireless channels in most existing works. As an alternative approach, single-carrier (SC) has also been proposed for LSA systems due to its low implementation complexity. In this article, a comprehensive comparison between LSA-OFDM and LSA-SC is presented, which is of interest to the waveform design for the next generation wireless systems.
The combination of energy harvesting and large-scale multiple antenna technologies provides a promising solution for improving the energy efficiency (EE) by exploiting renewable energy sources and reducing the transmission power per user and per antenna. However, the introduction of energy harvesting capabilities into large-scale multiple antenna systems poses many new challenges for energy-efficient system design due to the intermittent characteristics of renewable energy sources and limited battery capacity. Furthermore, the total manufacture cost and the sum power of a large number of radio frequency (RF) chains can not be ignored, and it would be impractical to use all the antennas for transmission. In this paper, we propose an energy-efficient antenna selection and power allocation algorithm to maximize the EE subject to the constraint of users quality of service (QoS). An iterative offline optimization algorithm is proposed to solve the non-convex EE optimization problem by exploiting the properties of nonlinear fractional programming. The relationships among maximum EE, selected antenna number, battery capacity, and EE-SE tradeoff are analyzed and verified through computer simulations.
We propose a regularized zero-forcing transmit precoding (RZF-TPC) aided and distance-based adaptive coding and modulation (ACM) scheme to support aeronautical communication applications, by exploiting the high spectral efficiency of large-scale antenna arrays and link adaption. Our RZF-TPC aided and distance-based ACM scheme switches its mode according to the distance between the communicating aircraft. We derive the closed-form asymptotic signal-to-interference-plus-noise ratio (SINR) expression of the RZF-TPC for the aeronautical channel, which is Rician, relying on a non-centered channel matrix that is dominated by the deterministic line-of-sight component. The effects of both realistic channel estimation errors and of the co-channel interference are considered in the derivation of this approximate closed-form SINR formula. Furthermore, we derive the analytical expression of the optimal regularization parameter that minimizes the mean square detection error. The achievable throughput expression based on our asymptotic approximate SINR formula is then utilized as the design metric for the proposed RZF-TPC aided and distance-based ACM scheme. Monte-Carlo simulation results are presented for validating our theoretical analysis as well as for investigating the impact of the key system parameters. The simulation results closely match the theoretical results. In the specific example that two communicating aircraft fly at a typical cruising speed of 920 km/h, heading in opposite direction over the distance up to 740 km taking a period of about 24 minutes, the RZF-TPC aided and distance-based ACM is capable of transmitting a total of 77 Gigabyte of data with the aid of 64 transmit antennas and 4 receive antennas, which is significantly higher than that of our previous eigen-beamforming transmit precoding aided and distance-based ACM benchmark.
In order to meet the demands of `Internet above the clouds, we propose a multiple-antenna aided adaptive coding and modulation (ACM) for aeronautical communications. The proposed ACM scheme switches its coding and modulation mode according to the distance between the communicating aircraft, which is readily available with the aid of the airborne radar or the global positioning system. We derive an asymptotic closed-form expression of the signal-to-interference-plus-noise ratio (SINR) as the number of transmitting antennas tends to infinity, in the presence of realistic co-channel interference and channel estimation errors. The achievable transmission rates and the corresponding mode-switching distance-thresholds are readily obtained based on this closed-form SINR formula. Monte-Carlo simulation results are used to validate our theoretical analysis. For the specific example of 32 transmit antennas and 4 receive antennas communicating at a 5 GHz carrier frequency and using 6 MHz bandwidth, which are reused by multiple other pairs of communicating aircraft, the proposed distance-based ACM is capable of providing as high as 65.928 Mbps data rate when the communication distance is less than 25,km.
Large-scale distributed-antenna system (L-DAS) with very large number of distributed antennas, possibly up to a few hundred antennas, is considered. A few major issues of the L-DAS, such as high latency, energy consumption, computational complexity, and large feedback (signaling) overhead, are identified. The potential capability of the L-DAS is illuminated in terms of an energy efficiency (EE) throughout the paper. We firstly and generally model the power consumption of an L-DAS, and formulate an EE maximization problem. To tackle two crucial issues, namely the huge computational complexity and large amount of feedback (signaling) information, we propose a channel-gain-based antenna selection (AS) method and an interference-based user clustering (UC) method. The original problem is then split into multiple subproblems by a cluster, and each clusters precoding and power control are managed in parallel for high EE. Simulation results reveal that i) using all antennas for zero-forcing multiuser multiple-input multiple-output (MU-MIMO) is energy inefficient if there is nonnegligible overhead power consumption on MU-MIMO processing, and ii) increasing the number of antennas does not necessarily result in a high EE. Furthermore, the results validate and underpin the EE merit of the proposed L-DAS complied with the AS, UC, precoding, and power control by comparing with non-clustering L-DAS and colocated antenna systems.
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