Lens Antenna Subarrays in mmWave Hybrid MIMO Systems

Karabacak, Murat; Arslan, Hüseyin; Mumcu, Gökhan

doi:10.1109/access.2020.3041633

Cited by 12 publications

(16 citation statements)

References 42 publications

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“…The design of a beamforming system for a large antenna array, as in massive MIMO [10]- [12], with only a single-lens antenna presents some difficulties, including power leakage problem [13], the large focal depth of the lens [14], and the lack of scalability, since a larger lens must be redesigned when the number of antenna elements changes. Therefore, dividing the aperture area occupied by a large single lens into smaller lenses is proposed in [15]- [17] under the name of lens antenna subarray (LAS) to obtain a competitive system in terms of RF design feasibility and power consumption reduction with minimal impact on per-chain capacity.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…In order to investigate the performance of the hybrid LAS-MIMO architecture shown in Figure 1(a), an analog/digital precoding technique was used based on an exhaustive search in [17]. The results in [17] show that the hybrid LAS architecture remarkably improves spectral efficiency and energy efficiency compared to a single-lens system under various mmWave channel conditions. Compared to a system without a lens array, i.e., hybrid traditional array (TA)-MIMO architecture [3], the LAS design shows a significant improvement in energy efficiency at sufficient data rate levels.…”

Section: Introductionmentioning

confidence: 99%

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Energy and Spectral-Efficient Lens Antenna Subarray Design in MmWave MIMO Systems

2022

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Lens antenna subarray (LAS) is one of the recently introduced technologies for future wireless networks that significantly improves the energy efficiency of multiple-input multiple-output (MIMO) systems while achieving higher spectral efficiency compared to single-lens MIMO systems. However, a control mechanism for the design of LAS-MIMO is considered a challenging task to efficiently manage the network resources and serve multiple users in the system. Therefore, a sub-grouped LAS-MIMO architecture along with a hybrid precoding algorithm are proposed in this paper to reduce the cost and hardware overhead of traditional hybrid MIMO systems. Specifically, the LAS structure is divided into sub-groups to serve multiple users with different requirements, and an optimization problem based on the achievable sum-rate is formulated to maximize the spectral efficiency of the system. By splitting the sum-rate problem into sub-rate optimization problems, we develop a low-complexity hybrid precoding algorithm to effectively control the proposed architecture and maximize the achievable sum-rate of each subgroup. The proposed precoding algorithm selects the beam of each lens from a predefined set within a subgroup that maximizes the subgroup sum-rate, while the phase shifters and digital precoders in each subgroup are computed independently. The link between subgroups is updated based on successive interference cancelation to minimize interference between users of different subgroups. Our analysis and simulation results show that the proposed precoding algorithm of the sub-grouped LAS-MIMO architecture performs almost as well as traditional fully-connected hybrid MIMO systems in terms of spectral efficiency at low and high signal-tonoise ratio (SNR). It also outperforms traditional fully-connected and sub-connected hybrid MIMO systems in terms of energy efficiency, even when a large number of lenses are used.INDEX TERMS Lens antenna subarray (LAS), sub-grouped, MIMO, mmWave, hybrid precoding, energy efficiency, spectral efficiency.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Energy and Spectral-Efficient Lens Antenna Subarray Design in MmWave MIMO Systems

2022

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“…considering a limited number of RF chains, while the diversity gains provided by the massive MIMO schemes are exploited with digital baseband processing [10]- [12]. There exist different alternatives for implementing the RF stage, such as the use of switches, phase shifters or lens [8], [13], as well as different connection structures [14]- [16].…”

Section: Introductionmentioning

confidence: 99%

Rank Constrained Precoding for the Downlink of mmWave Massive MIMO Hybrid Systems

González-Coma¹,

Fresnedo

Castedo

2021

IEEE Access

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The hybrid design of precoding schemes for millimeter-wave communications allows exploiting the gains by using large antenna array with an affordable hardware cost and power consumption. In this work, we present a novel design strategy based on limiting the rank of the fully digital solutions before their decomposition into the analog and digital baseband components. This rank constraint on the digital formulation leads to a joint precoding and scheduling scheme where the number of allocated streams is limited according to the hardware constraints. In this way, the proposed approach can significantly reduce the performance losses caused by the direct decomposition of the unconstrained digital precoders. The resulting rank-constrained problems for the considered scenario are not convex and difficult to sort out. However, we propose several algorithms to compute the rank-constrained digital solutions with the help of the uplink-downlink duality for the achievable sum-rate. The obtained results show that this strategy achieves considerably higher sum-rates regardless of the channel conditions or available hardware resources.INDEX TERMS Hybrid transceiver, Massive MIMO, mmWave communications, rank-constrained optimization.

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“…Moreover, massive MIMO under microwave case is often constrained by limited space, because it requires the deployment of hundreds or thousands of antennas 15,16 . Whereas mmWave has wavelength of 1 to 10 mm, which makes it feasible that hundreds of antennas are employed simultaneously 17,18 …”

Section: Introductionmentioning

confidence: 99%

Optimization of the quality‐to‐power ratio of scalable video code video transmission in millimeter‐wave massive multiple‐input multiple‐output systems

Zhang

Zhao

Cheng

et al. 2021

Trans Emerging Tel Tech

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Consider a millimeter‐wave (mmWave) massive multiple‐input multiple‐output (MIMO) system, where a base station (BS) relying on discrete lens antenna (DLA) array transmits scalable video code (SVC) video to multiple single‐antenna vehicles. Taking into account both the video quality for vehicles and the communication resource consumption of BS, we define a new metric given by the quality of received video to the power consumption ratio (QPR) in order to measure the system efficiency. The objective of this article is to maximize the minimum QPR among vehicles by designing the antenna selection and power allocation scheme, while ensuring the constraints of total transmit power and DLA array structure. Due to the piecewise form of the video quality function, it is intractable to solve the formulated problem, which is therefore decomposed into antenna selection and power allocation subproblems. A maximum equivalent channel gain (MECG) algorithm and an iteration algorithm are proposed for antenna selection subproblem with different complexities, respectively; while an optimal power allocation (OPA) algorithm is designed by analyzing three cases of transmit power constraints. Simulation results indicate that the proposed MECG algorithm has moderate performance with low‐complexity, while the OPA algorithm can help to achieve the optimal QPR in contrast to other algorithms.

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Lens Antenna Subarrays in mmWave Hybrid MIMO Systems

Cited by 12 publications

References 42 publications

Energy and Spectral-Efficient Lens Antenna Subarray Design in MmWave MIMO Systems

Energy and Spectral-Efficient Lens Antenna Subarray Design in MmWave MIMO Systems

Rank Constrained Precoding for the Downlink of mmWave Massive MIMO Hybrid Systems

Optimization of the quality‐to‐power ratio of scalable video code video transmission in millimeter‐wave massive multiple‐input multiple‐output systems

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