Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems

Alkhateeb, Ahmed; Heath, Robert W.

doi:10.1109/tcomm.2016.2549517

Cited by 508 publications

(480 citation statements)

References 68 publications

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“…In this simulation, The number of transmitted streams is fixed at 3 S N = . As can be seen from this figure, the suboptimal method proposed in this study exhibits a better performance than the method proposed in [29], but shows almost the same performance with the method proposed in [20]. This performance is quite good for a suboptimal method.…”

Section: Computer Simulationsmentioning

confidence: 51%

“…Since mmW propagation enviorement is well characterized by a clustered channel model, mmW channel model at almostly all works in the literature such as [3,[14][15][16][17][18][19][20] is based on Saleh-Valenzualle geometric channel model in [21]. Since the author believes that the best representation among them is the representation in [20], he adopt the same channel model with L clusters, each of which has a time delay τ l ∈R , and Angle of Arrival (AoA) and Angle of Departure (AoD) θ l ,φ l ∈[0,2π ] . Each ray has a relative time delay τ r l , relative angle of arrival and departure shift ψ r l , ϕ r l , and complex path gain α r l .…”

Section: Channel Modelmentioning

confidence: 99%

“…{ } under the constraints in (3) gives optimum hybrid precoder matrices RF P and ( ) BB m P , and combiner matrices RF C and ( ) BB m C , but it still requires needs M -dimensional non-convex optimization such as in [19] and [20]. However, this problem can be more easily solved when channel state information is available in MS side (this assumption is a reasonable, since channel reciprocity can be assumed when BS communicates to MS in time division duplexing mode).…”

Section: Proposed Suboptimal Transceiver Designmentioning

confidence: 99%

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Suboptimal Frequency-Selective Transceiver Design for Multicarrier Millimeter Wave MIMO Systems

Kabaoglu¹

2018

IU-JEEE

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With intelligent devices taking an important role in our lives, demand for high data rate and system capacity is increasing day by day. The Long Term Evolution (LTE) standard, which is the standard of today's fourth-generation (4G) systems, has been able to meet these demands to a certain extent by using Orthogonal Frequency Division Multiplexing (OFDM) and Multiple-Input Multiple-Output (MIMO) technology on a network designed from the outset. However, with the extraordinary demand for applications that require more bandwidth, such as very high resolution video applications, the contradiction between capacity requirements and spectrum constraints has become more apparent. It is not possible to meet this demand with existing cellular network technology, which has a very limited bandwidth and a fairly crowded spectrum. Due to the aforementioned bandwidth bottleneck, research has been initiated to provide innovative solutions for 5G cellular communication systems to support the total mobile user network traffic expected to increase 1000 times by 2020 [1]. Millimeter wave (mmW) communication for physical layers of personal Wireless Area Networks (WPAN), Local Area Networks (LAN) and Metropolitan Area Networks (MAN) has already been standardized [2,3] and has a data rate potential of Gbits at the moment, mmW communication has also become a strong candidate for 5G cellular networks.The mmW band is the frequency range defined as 30 GHz -300 GHz (3 GHz to 30 GHz according to some studies). There are several advantages to be gained by using mmW band in 5G cellular networks. The first one of them is that the mmW band provides a wide spectrum. The other is that the communication in this band is short-range one due to the severe path loss, and thus it is possible to reuse the frequency at short distances and hence it is possible to extremely increase the capacity. Another is that very high data rates can be achieved by communicating with antenna arrays consisting of several ABSTRACTFifth-generation (5G) cellular communication systems aim to obtain a higher data rate, decreased latency time, higher performance even at high mobility speeds, decreased system complexity, lower transmission cost, and an increased system capacity and coverage area. Many of these goals can be achieved because of the studies devoted to the physical layer of 5G cellular networks. In this respect, solutions to the problems of beamforming (steering and precoding or precoding and combining) and channel estimation that are encountered in the physical layer of 5G cellular networks are the key points to achieve the aforementioned goals. Thus, a two-stage beamforming method is proposed in this study. The proposed method is a suboptimal method that minimizes the difference between outputs obtained when fully digital and hybrid beamforming methods are used. The analytical results, which are validated through simulations, demonstrate that the proposed method is an effective solution and, hence, the preferred beamforming approach for 5G millimeter wave band-b...

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Section: Computer Simulationsmentioning

confidence: 51%

Section: Channel Modelmentioning

confidence: 99%

Section: Proposed Suboptimal Transceiver Designmentioning

confidence: 99%

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Suboptimal Frequency-Selective Transceiver Design for Multicarrier Millimeter Wave MIMO Systems

Kabaoglu¹

2018

IU-JEEE

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“…As a result, the analog signal processing (e.g., precoding) cannot be adaptively adjusted according to different frequencies. This will lead to more challenges in signal processing design, which requires future investigation, but some pioneering works can be found in [137], [140]. The narrowband system model of the hybrid architecture can be presented as [117] …”

Section: B Channel Estimation With Hybrid Architecturementioning

confidence: 99%

Millimeter Wave Communications for Future Mobile Networks

Xiao

Mumtaz

Huang

et al. 2017

IEEE J. Select. Areas Commun.

961

530

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Abstract-Millimeter wave (mmWave) communications have recently attracted large research interest, since the huge available bandwidth can potentially lead to rates of multiple Gbps (gigabit per second) per user. Though mmWave can be readily used in stationary scenarios such as indoor hotspots or backhaul, it is challenging to use mmWave in mobile networks, where the transmitting/receiving nodes may be moving, channels may have a complicated structure, and the coordination among multiple nodes is difficult. To fully exploit the high potential rates of mmWave in mobile networks, lots of technical problems must be addressed. This paper presents a comprehensive survey of mmWave communications for future mobile networks (5G and beyond). We first summarize the recent channel measurement campaigns and modeling results. Then, we discuss in detail recent progresses in multiple input multiple output (MIMO) transceiver design for mmWave communications. After that, we provide an overview of the solution for multiple access and backhauling, followed by analysis of coverage and connectivity. Finally, the progresses in the standardization and deployment of mmWave for mobile networks are discussed.

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“…Mmwave's high carrier frequency facilitates packing a large number of antenna elements in a physically limited space, thus enabling massive MIMO to be feasible. In addition, due to the ability to cope with severe frequency-selective fading channel without complex equalization, orthogonal frequency division multiplexing (OFDM) has been considered to joint massive MIMO in mmWave systems [11], [12].…”

Section: Introductionmentioning

confidence: 99%

A low cost interpolation based detection algorithm for medium-size massive MIMO-OFDM systems

Fang

Huang

et al. 2017

2017 17th International Symposium on Communications and Information Technologies (ISCIT)

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Abstract-The great potential of exploiting millimeter wave (mmwave) frequency spectrum for emerging fifth-generation (5G) wireless networks has motivated the study of massive multipleinput multiple-output (MIMO) for achieving high data rate. For medium-size massive MIMO with orthogonal frequency division multiplexing (OFDM) uplink systems, the minimum mean square error (MMSE) based soft-output detector is often used due to its better bit error rate (BER) performance compared to the matched filter detector. Although the multipath channel can be converted into a set of parallel flat-fading channels by using OFDM thus reducing the complexity of receiver design, the tone by tone (per subcarrier) detection methods based on the state-of-the-art low complexity MMSE still incur considerably high computational complexity since the number of tones is typically very large. To reduce the complexity, the interpolationbased matrix inversion algorithms for small-size MIMO-OFDM systems have been proposed, which compute the matrix inversion by interpolating separately the adjoint and determinant. In this paper, we find that the (regularized) Gram matrix inversions have strong correlation between different subcarriers. By exploiting this strong correlation, we propose a linear interpolation based MMSE detection algorithm that directly interpolates the inverted MMSE matrices for a small number of subcarriers to obtain matrix inversions for all other subcarriers, thereby significantly reducing the number of matrix inversion required. Extensive simulations show that with small BER performance loss compared to the exact MMSE detector, the proposed algorithm can reduce the complexity to the level of the matched filter algorithm.

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Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems

Cited by 508 publications

References 68 publications

Suboptimal Frequency-Selective Transceiver Design for Multicarrier Millimeter Wave MIMO Systems

Suboptimal Frequency-Selective Transceiver Design for Multicarrier Millimeter Wave MIMO Systems

Millimeter Wave Communications for Future Mobile Networks

A low cost interpolation based detection algorithm for medium-size massive MIMO-OFDM systems

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