Elsevier

Ad Hoc Networks

Volume 111, 1 February 2021, 102358
Ad Hoc Networks

Design and implementation of beamformed physical downlink control channel for 4G massive MIMO systems

https://doi.org/10.1016/j.adhoc.2020.102358Get rights and content

Abstract

The Full Dimension-MIMO (FD-MIMO) technology is capable of achieving huge improvements in network throughput with simultaneous connectivity of a large number of mobile wireless devices, unmanned aerial vehicles, and the Internet of Things (IoT). In the Long Term Evolution (LTE), with a large number of antennae at the base station and the ability to perform beamforming, the capacity of the physical downlink shared channel (PDSCH) has increased a lot. However, the current 3rd Generation Partnership Project (3GPP) specifications of the LTE do not allow the base station to perform any beamforming techniques for the physical downlink control channel (PDCCH). Hence, PDCCH has neither the capacity nor the coverage of PDSCH. Therefore, PDCCH capacity still limits the performance of a network, as it dictates the number of users that a base station can schedule at a given time instant. In Release 11, 3GPP introduced enhanced PDCCH (EPDCCH) to increase the PDCCH capacity at the cost of sacrificing the PDSCH resources. The problem of enhancing the PDCCH capacity within the available control channel resources has not been addressed yet in the literature. Hence, in this paper, we propose a novel beamformed PDCCH (BF-PDCCH) design which is aligned to the 3GPP specifications and requires simple software changes at the base station. For the evaluation of the proposed BF-PDCCH, we model various link abstractions. We evaluate them through link-level simulations and then use all these abstractions in the system-level simulations. We show that the proposed BF-PDCCH achieves significant improvement in network throughput and outperforms the current state of the art algorithms, PDCCH, and EPDCCH schemes.

Introduction

Full Dimension-Multi Input Multi Output (FD-MIMO) is a key technology in achieving larger network throughputs by simultaneously connecting a large number of devices. This has been an active topic in the standardization activities of 3rd Generation Partnership Project (3GPP). In FD-MIMO, a two-dimensional antenna array structure is used that helps in beamforming along both elevation and azimuth directions. With this kind of beamforming, an enhanced multi-user MIMO transmission can be done at the base station to achieve a multi-fold enhancement in the network throughput [1]. From Release 8, 3GPP has continuously evolved its specifications to enhance the multi-user MIMO feature and thus, enable a large number of users to be supported by the base station [2], [3]. In Release 13, 3GPP specifications support both the azimuth and elevation beamforming for the data channel. Based on a newly introduced channel state information-reference signals (CSI-RS) and the demodulation reference signals (DMRS), the base station performs beamforming for the data channel. With this kind of beamforming, 2–3.6 times gain in the cell throughput is achieved [1].

In Long Term Evolution (LTE), the downlink physical layer has five channels [4], [5], [6]. They are physical broadcast channel (PBCH) for broadcasting the system information, physical control format indicator channel (PCFICH) for defining the structure of the control channel, physical HARQ indicator channel (PHICH) for conveying the ack/nack, physical downlink control channel (PDCCH) for carrying the control information and physical downlink shared channel (PDSCH) for transmitting the user intended data. In this paper, we focus on PDCCH, which carries the downlink control information (DCI). DCI conveys the information required to decode the user intended data. As explained later in Section 4, the PDCCH region in any subframe is limited to 3 symbols [6] and hence, can accommodate a limited number of DCIs in a transmission time interval (TTI). Thus, the PDCCH effectively indicates the number of users scheduled in any TTI.

In Release 8 3GPP specifications, PDCCH and PDSCH rely on cell-specific reference signals (CRS) for the channel estimation. Whereas from Release 13, the PDSCH supports beamforming and hence, has DMRS for the channel estimation. Fig. 1 presents the transmission of the physical layer signals in both Release 8 and 13. CRS is common for all the users, and beamforming CRS would impact the performance of cell search and synchronization. Thus, with the current 3GPP specifications of LTE, the control channel does not possess the benefits of beamforming. Note that a user can decode the data channel only after decoding a DCI. Thus, even though the beamforming allows to schedule more users in PDSCH, the PDCCH has a limited capacity and has become a bottleneck in increasing the network throughput. In Release 11, to enhance the PDCCH capacity, 3GPP introduced enhanced PDCCH (EPDCCH) design which uses the concepts of beamforming. However, the EPDCCH has to be transmitted in the resources of the data channel, as shown in Fig. 2. Further, the location of the EPDCCH has to be conveyed a priori to the user.

The availability of the large antennae structure with the FD-MIMO is never exploited in the context of the LTE-PDCCH. This is because beamforming requires some feedback from the user. However, the control channel itself is the first communication link where the user performs blind decoding for the DCI. Improving the PDCCH capacity by exploiting the large antennae structure has a high impact on network throughput and has never been considered in the literature. Hence, in this paper, we propose a novel beamformed PDCCH (BF-PDCCH) design which addresses all the above-said issues.

The rest of the paper is organized as follows. In Section 2, we present the motivation and summary of the contributions in this paper. Section 3 presents some of the related work in the literature. In Section 4, we explain the current physical downlink control channel structure and the enhancements as per 3GPP specifications. Section 5 explains the antenna array structure, the design, and the implementation of the beam weights. In Section 6, we present the proposed BF-PDCCH design and its performance analysis. Section 7 explains the procedures and the algorithms for the implementation of the proposed scheme. In Section 8, we present the simulation model and discuss the numerical results. We present some concluding remarks and possible future work in Section 9.

Section snippets

Motivation and contributions

Currently, there has been a wide commercial deployment of massive MIMO across the world [7], [8]. As reported in [8], the LTE massive MIMO achieves 2–3 times gain in the network capacity on the field. Removing the control channel bottleneck and enhancing the control channel capacity could thus further maximize the network capacity. Motivated by this, we propose a novel beamformed PDCCH design in this paper.

The main contributions of the paper are as follows.

  • We propose the BF-PDCCH design for LTE

Related work

In [9], authors have presented an algorithm to optimally schedule the users in PDCCH and thus, increase the control channel capacity. In [10], authors have proposed a novel method of allocation for cell radio network temporary identifiers and increase the control channel capacity. In [11], authors propose power allocation techniques to improve the control channel capacity. In [12], authors have presented a joint control and shared channel scheduling for 3GPP Narrowband-IoT systems. However,

3GPP physical downlink control channel

The PDCCH is present in the first few orthogonal frequency division multiplexing (OFDM) symbols of every subframe. The first OFDM symbol has PCFICH, PHICH, and PDCCH multiplexed in it. PCFICH defines the number of symbols for PDCCH. DCI is the payload transmitted in PDCCH. DCI carries the information required for decoding the user data, location of uplink scheduling, modulation and coding scheme, and random access responses. There are various DCI formats for each purpose. Before transmission,

Design and implementation of beams for BF-PDCCH

The antenna array structure considered for generating beams for the BF-PDCCH is shown in Fig. 5. As per 3GPP specifications [19], the rectangular panel array is described by the following tuple (Mg,Ng,M,N,P), where, Mg and Ng represent the number of panels in the vertical and horizontal direction, M and N represents the number of antenna elements with the same polarization in the vertical and horizontal direction in each panel, and P represents the panel is either single polarized (P=1) or

Proposed beamformed PDCCH design

In this section, we initially explain the constraints for designing beamformed PDCCH as per 3GPP specifications. Then, we propose a novel beamformed PDCCH design and in the end, we discuss and analyze the performance of the proposed scheme.

In multi-user MIMO, initially, the best beams for each user are identified (a clear explanation of identifying the best beam for a user is provided in Section 7.2). These beams are spatially well separated, and thus, the transmission is done simultaneously in

Procedures for the implementation and evaluation of BF-PDCCH

A system-level simulation typically abstracts link-layer characteristics. For this, a block error rate (BLER) vs. signal to interference plus noise ratio (SINR) curve is generated for different modulation and coding schemes which are thereafter used in a system-level simulation. For the proposed BF-PDCCH evaluation, we need to further abstract the channel estimation errors. Hence, we initially present the link-level simulations and conclude on the abstraction to be used in the system-level

Simulation results and discussion

The parameters for the system-level simulations are considered as per the 3GPP specifications [24] and are presented in Table 2. We have modeled the link abstractions for allocating AL based on the SINR of each user. We have also considered the SINR degradation happening because of the CRS re-use. For comparing the performance of the proposed BF-PDCCH, we implement the current 3GPP LTE PDCCH and EPDCCH schemes. For the EPDCCH case, we consider an extra four PRBs of resources available from the

Conclusion and future work

We proposed a novel beamforming design for the control channel of LTE, which is aligned to the current 3GPP specifications and requires no changes at the user end. The proposed design removes the control channel bottleneck and maximizes the network capacity. Unlike the current 3GPP mechanisms of enhancing the capacity, the proposed scheme does not use additional resources from the data channel. We efficiently use the large antenna structure available at the base station and schedule more users

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Pavan Reddy M. received the B.Tech. degree from the ACE Engineering College, India, in 2014, and the M.Tech. degree in electrical engineering from IIT Hyderabad, Hyderabad, India, in 2018. He is currently a Ph.D. student at IIT Hyderabad. His research interests include physical-layer algorithms and the development of prototypes for fifth-generation systems. He was a recipient of the Excellence in Research Award at IIT Hyderabad in 2018.

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  • Pavan Reddy M. received the B.Tech. degree from the ACE Engineering College, India, in 2014, and the M.Tech. degree in electrical engineering from IIT Hyderabad, Hyderabad, India, in 2018. He is currently a Ph.D. student at IIT Hyderabad. His research interests include physical-layer algorithms and the development of prototypes for fifth-generation systems. He was a recipient of the Excellence in Research Award at IIT Hyderabad in 2018.

    Harish Kumar D. received the B.Tech. degree from the RGUKT, RK Valley, India, in 2014, and the M.Tech. degree in electrical engineering from IIT Hyderabad, Hyderabad, India, in 2016. He is currently a Research Engineer at WiSig Networks, a start-up incubated at IIT Hyderabad. His research interests include wireless communications, digital signal processing, coding theory, algorithm design, and evaluation of modems.

    SaiDhiraj Amuru (S’12–M’15) received the B.Tech. degree in electrical engineering from the Indian Institute of Technology Madras, Chennai, India, and the Ph.D. degree in electrical and computer engineering from Virginia Tech, Blacksburg, VA, USA, in 2009 and 2015, respectively. From 2009 to 2011, he was with Qualcomm, India, as a Modem Engineer. He visited the Networks, Economics, Communication Systems, Informatics, and Multimedia Research Laboratory, University of California, Los Angeles, CA, USA, in 2014. He is currently an Adjunct Faculty with the Department of Electrical Engineering, IIT Hyderabad, Hyderabad, India. His research interests include wireless communications, cognitive radio, statistical signal processing, and online learning.

    Kiran Kuchi received the B.Tech. degree in electronics and communications engineering from the Sri Venkateswara University College of Engineering, Tirupati, India, in 1995, and the M.S. and Ph.D. degrees in electrical engineering from The University of Texas at Arlington, Arlington, TX, USA, in 1997 and 2006, respectively. From 2000 to 2008, he was with Nokia Research, Irving, TX, where he contributed to the development of global system for mobile communication/EDGE, WiMax, and long-term evolution systems. From 2008 to 2011, he was with the Centre of Excellence in Wireless Technology, where he led fourth-generation research and standardization efforts. He was also an Adjunct Faculty with the Department of Electric Engineering, IIT Madras, Chennai, India. He is currently a Professor with the Department of Electrical Engineering, IIT Hyderabad, Hyderabad, India. He holds more than 20 U.S. patents. His current research interests include physical-layer algorithms and the development of prototypes for fifth-generation systems.

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