Joint Frame Design, Resource Allocation and User Association for Massive MIMO Heterogeneous Networks With Wireless Backhaul

Feng, Mingjie; Mao, Shiwen; Jiang, Tao

doi:10.1109/twc.2017.2787139

Cited by 47 publications

(54 citation statements)

References 38 publications

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“…According to (33) and (34), we find that the CUEs have less interferences in the denominators of γ C,RP k and γ C,SP k than those of the V2V pairs, due to the CUEs' orthogonal pilot allocation.…”

Section: Performance Analysis Of Cuesmentioning

confidence: 91%

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Joint Frame Design and Resource Allocation for Ultra-Reliable and Low-Latency Vehicular Networks

Yang

Zheng

Qian

2020

IEEE Trans. Wireless Commun.

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The rapid development of the fifth generation mobile communication systems accelerates the implementation of vehicle-to-everything communications. Compared with the other types of vehicular communications, vehicle-to-vehicle (V2V) communications mainly focus on the exchange of driving safety information with neighboring vehicles, which requires ultra-reliable and low-latency communications (URLLCs). However, the frame size is significantly shortened in V2V URLLCs because of the rigorous latency requirements, and thus the overhead is no longer negligible compared with the payload information from the perspective of size. In this paper, we investigate the frame design and resource allocation for an urban V2V URLLC system in which the uplink cellular resources are reused at the underlay mode. Specifically, we first analyze the lower bounds of performance for V2V pairs and cellular users based on the regular pilot scheme and superimposed pilot scheme. Then, we propose a frame design algorithm and a semi-persistent scheduling algorithm to achieve the optimal frame design and resource allocation with the reasonable complexity. Finally, our simulation results show that the proposed frame design and resource allocation scheme can greatly satisfy the URLLC requirements of V2V pairs and guarantee the communication quality of cellular users. Index TermsVehicular networks (VNET), vehicle-to-vehicle (V2V), ultra-reliable and low-latency communications (URLLC), finite blocklength theory, massive MIMO. Haojun Yang and Kan Zheng are with the Intelligent Computing and Communications (IC 2 ) Lab, Wireless Signal Processing and Networks (WSPN) Lab,

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Section: Performance Analysis Of Cuesmentioning

confidence: 91%

“…Theorem 2: For the urban V2V URLLC system operating with the underlay mode, a lower bound of the CUEs' SINR averaged over the pilot allocation is given by [26], [33]:…”

Section: Performance Analysis Of Cuesmentioning

confidence: 99%

Joint Frame Design and Resource Allocation for Ultra-Reliable and Low-Latency Vehicular Networks

Yang

Zheng

Qian

2020

IEEE Trans. Wireless Commun.

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“…In [14], [15], the authors used stochastic geometry to derive the rate coverage probability and compute the optimal proportion of inband and out-of-band FD SCs in the network which maximize the UE rates, and energy efficiency, respectively. Finally, the authors in [16] investigated an optimization approach to maximize the sum-rate of the UEs under capacity constrained backhaul and by considering the length of the pilot sequences used for the channel state information (CSI) acquisition.…”

Section: A Background and Related Workmentioning

confidence: 99%

“…To the best of the authors knowledge, we also compare for the first time the performance of mMIMO s-BH and mMIMO DA architectures. Differently from the previous works [13]- [16], our work accounts for a path loss model with LoS and Non-LoS (NLoS) transition regions in both backhaul and access links. Moreover, we consider the pilot contamination effect on the signal-to-interferenceplus-noise ratio (SINR), when mMIMO is used.…”

Section: B Motivation and Contributionmentioning

confidence: 99%

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5G Massive MIMO Architectures: Self-Backhauled Small Cells Versus Direct Access

Bonfante

Giordano

Liu

et al. 2019

IEEE Trans. Veh. Technol.

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In this paper, we focus on one of the key technologies for the fifth-generation wireless communication networks, massive multiple-input-multiple-output (mMIMO), by investigating two of its most relevant architectures: 1) to provide in-band wireless backhauling to a dense deployment of self-backhauled small cells (SCs) acting as communication relays to end-users, and 2) to provide direct wireless access (DA) to end-users. Through comprehensive 3GPP-based system-level simulations and analytical formulation, we show the end-to-end user rates achievable with these two architectures. Different from the existing work, we provide results for two strategies of self-backhauled SCs deployments, namely random and ad-hoc. Where in the latter SCs are purposely positioned close to UEs to achieve line-ofsight (LoS) access links. We also show the optimal backhaul and access time resource partition due to the in-band self-backhauling operations. For the mMIMO DA, we consider the implication of different pilot reuse schemes for the channel state information (CSI) acquisition, associated overhead and contamination effects. We find that the ad-hoc deployment of self-backhauled SCs closer to the users (UEs) with optimal resource partition and with directive antenna patterns, provides rate improvements for celledge UEs that amount to 30%, and a tenfold gain as compared to mMIMO DA architecture with pilot reuse 3 and reuse 1, respectively. On the other hand, mMIMO s-BH underperforms mMIMO DA above the median of the UE rates when the UEs are in the center of the cell, and the effect of pilot contamination is mitigated.Index Terms-5G mobile communication, massive MIMO, wireless backhaul, small cell deployment, network capacity.

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MassiveMIMO

Zhang¹,

Mao²

2019

Wiley 5G Ref

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Massive MIMO has been regarded as a promising technique for 5G wireless communication networks. It equips the base station (BS) with a large number of antennas to serve a set of user equipment (UEs) simultaneously. Due to channel hardening, the uncorrelated noise and the small‐scale fading can be eliminated. As a result, the transmitted signal can be directed into very focused areas, which brings orders‐of‐magnitude improvements in both spectral efficiency and energy efficiency with simple (linear) processing. In this chapter, we present a comprehensive overview of the state‐of‐the‐art research on massive MIMO. We begin with an information theoretic analysis to illustrate the advantages of massive MIMO. Then, we introduce both the physical layer and networking issues of massive MIMO. The integration of other 5G technologies with massive MIMO is also reviewed. Finally, we conclude this article with a discussion of challenges and future research topics.

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Joint Frame Design, Resource Allocation and User Association for Massive MIMO Heterogeneous Networks With Wireless Backhaul

Cited by 47 publications

References 38 publications

Joint Frame Design and Resource Allocation for Ultra-Reliable and Low-Latency Vehicular Networks

Joint Frame Design and Resource Allocation for Ultra-Reliable and Low-Latency Vehicular Networks

5G Massive MIMO Architectures: Self-Backhauled Small Cells Versus Direct Access

MassiveMIMO

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