5G backhaul

This study examines fixed/mobile convergence from the perspective of
increasing European broadband connectivity through dense networks of small cells. The analysis focuses on the practical side of assuring quality of service for 5G and EU-wide coverage through regulatory obligations for mobile broadband networks. The study examines not just quality of experience indicators for regulators but the framework needed to induce a major transformation of applications for industry verticals. It examines the architecture of dense small cell networks and the constraints imposed by the costs and limitations of backhaul, and proposes a phased implementation plan for the EU.

We consider the estimation of millimeter wave (mmWave) channel gains following the now well-established approach of sparse signal processing. Within that context, we offer two major contributions. The first is a complete frame-theoretical treatment of the sensing matrix design (beam management) problem, compactly described by a pair of Lemmas that together with efficient low-coherence frame construction algorithms offer a general solution for the optimal transmitter (Tx) and receiver (Rx) beamforming components of the sparse mmWave channel estimation problem. The second contribution is a pair of novel sparse recovery algorithms, which unlike the majority of sparse solvers found in the literature, is not based on the relaxation of 0-norm into an 1-norm, but rather on a smooth approximation of the 0-norm handled further via fractional programming (FPG). The two algorithms differ from each other in that in the first (slightly more accurate), the resulting convex problem is solved via interior point methods, while the second (stand-alone) makes use of the alternating direction method of multipliers (ADMM). As a bonus, an original ADMM variation of the well-known basis pursuit denoising (BPDN)-1-reweighted sparse solver is also given. Simulation results confirm the channel estimation accuracy improvements obtained by both contributions.

The volume of global mobile data traffic is expected to increase exponentially in the coming years. To enable this, disruptive solutions are required for 5th generation mobile networks (5G). Network capacity can be increased by enhancing spectral efficiency, cell density, as well as by procuring new spectrum. Considering the expected demand, all three will be essential. Millimeter wavelength (millimeter-wave) (30 GHz and above) spectrum was always known to be ample and underutilized, but was previously not considered favorable for mobile communications due to its radio propagation properties.While millimeter-waves offer more bandwidth than all of the spectrum below 6 GHz combined, they require a substantially different approach. A particular issue is the maximum length of a millimeter wave mobile access link; cell radii are estimated to be at most only hundreds of meters due to the unfavorable link budget. Millimeter waves will enable very dense cell layouts for extremely high network capacities.

In this paper, a novel full-duplex non-coherent (FD-NC) transmission scheme is developed for massive multiple-input multiple-output (mMIMO) systems using analog beamforming (ABF). We propose to use a structured Grassmannian constellation for the non-coherent communications that does not require channel estimation. Then, we design the transmit and receive ABF via the slow time-varying angle-of-departure (AoD) and angle-of-arrival (AoA) information, respectively. The ABF design targets maximizing the intended signal power while suppressing the strong self-interference (SI) occurred in the FD transmission. Also, the proposed ABF technique only needs a single transmit and receive RF chain to support large antenna arrays, thus, it reduces hardware cost/complexity in the mMIMO systems. It is shown that the proposed FD-NC offers a great improvement in bit error rate (BER) in comparison to both half-duplex noncoherent (HD-NC) and HD coherent schemes. We also observe that the proposed FD-NC both reduces the error floor resulted from the residual SI in FD transmission, and provides lower BER compared to the FD coherent transmission.

The presence of a super high rate, but also cost-efficient, easy-to-deploy, and scalable, backhaul/fronthaul framework is essential in the upcoming fifth-generation (5G) wireless networks & beyond. Motivated by the mounting interest in the unmanned flying platforms of various types including unmanned aerial vehicles (UAVs), drones, balloons, and high-altitude/medium-altitude/low-altitude platforms (HAPs/MAPs/LAPs), which we refer to as the networked flying platforms (NFPs), for providing communications services, and by the recent advances in free-space optics (FSO), this article investigates the feasibility of a novel vertical backhaul/fronthaul framework where the NFPs transport the backhaul/fronthaul traffic between the access and core networks via point-to-point FSO links. The performance of the proposed innovative approach is investigated under different weather conditions and a broad range of system parameters. Simulation results demonstrate that the FSO-based vertical backhaul/fronthaul framework can offer data rates higher than the baseline alternatives, and thus can be considered as a promising solution to the emerging backhaul/fronthaul requirements of the 5G+ wireless networks, particularly in the presence of ultra-dense heterogeneous small cells. The paper also presents the challenges that accompany such a novel framework and provides some key ideas towards overcoming these challenges. Index Terms-Free-space optics (FSO); 5G+ wireless networks; vertical backhaul/fronthaul; heterogeneous networks (HetNets); radio access network (RAN); networked flying platforms (NFPs); unmanned aerial vehicle (UAV); drones; low altitude platform (LAP); medium altitude platform (MAP); high altitude platform (HAP); link budget.

This paper develops a location based analog beamforming (BF) technique using compressive sensing (CS) to be feasible for millimeter wave (mmWave) wireless communication systems. The proposed scheme is based on exploiting the benefits of CS and localization to reduce mmWave beamforming (BF) complexity and enhance its performance compared with conventional mmWave analog BF techniques. CS theory is used to exploit the sparse nature of the mmWave propagation channel to estimate both the angle of departures (AoDs) and the angle of arrivals (AoAs) of the mmWave channel, and knowing the node location effectively reduces the number of BF vectors required for constructing the sensing matrix. Hence, a high accurate mmWave BF with a low setup time can be obtained. Simulation analysis confirms the high effectiveness of the proposed mmWave BF technique compared to the conventional exhaustive search BF and the CS based BF without localization using random measurements. I.

Codebook design is a key point in beam-forming which is necessary for millimetre Wave (mmWave) communication to compensate its huge free space path loss. In beam-forming codebook, the transmitter and the receiver cooperate to select the optimum pre-designed code vectors to satisfy robust, efficient, and reliable transmission link between two pairs. In our study, we propose a new codebook structure based on unique phase states. Based on the Array Factor (AF) and Signal-to-Noise Ratio (SNR), the proposed codebook is compared and evaluated with the uniform weighting codebook, circular array codebook, and IEEE 802.15.3c standard codebook. The results show that the proposed codebook achieves comparable SNR and array directivity with the IEEE 802.15.3c, but higher peak and wide dynamic range of SNR and better array directivity compared with the uniform weighting and circular antenna codebooks. Thus, the proposed codebook is expected to improve signal quality and increase user throughput significantly.

The rising number of technological advanced devices making network coverage planning very challenging tasks for network operators. The transmission quality between the transmitter and the end users has to be optimum for the best performance out of any device. Besides, the presence of coverage hole is also an ongoing issue for operators which cannot be ignored throughout the whole operational stage. Any coverage hole in network operators' coverage region will hamper the communication applications and degrade the reputation of the operator's services. Presently, there are techniques to detect coverage holes such as drive test or minimization of drive test. However, these approaches have many limitations. The extreme costs, outdated information about the radio environment and high time consumption do not allow to meet the requirement competently. To overcome these problems, we take advantage of Unmanned aerial vehicle (UAV) and Q-learning to autonomously detect coverage hole in a given area and then deploy UAV based base station (UAV-BS) by considering wireless backhaul with the core network and users demand. This machine learning mechanism will help the UAV to eliminate human-in-the-loop (HiTL) model. Later, we formulate an optimisation problem for 3D UAV-BS placement at various angular positions to maximise the number of users associated with the UAV-BS. In summary, we have illustrated a cost-effective as well as time saving approach of detecting coverage hole and providing on-demand coverage in this article.

Fifth generation (5G) and beyond-5G (B5G) systems expect coverage and capacity enhancements along with the consideration of limited power, cost and spectrum. Densification of small cells (SCs) is a promising approach to cater these demands of 5G and B5G systems. However, such an ultra dense network of SCs requires provision of smart backhaul and fronthaul networks. In this paper, we employ a scalable idea of using networked flying platforms (NFPs) as aerial hubs to provide fronthaul connectivity to the SCs. We consider the association problem of SCs and NFPs in a SC network and study the effect of practical constraints related to the system and NFPs. Mainly, we show that the association problem is related to the generalized assignment problem (GAP). Using this relation with the GAP, we show the NP-hard complexity of the association problem and further derive an upper bound for the maximum achievable sum data rate. Linear Programming relaxation of the problem is also studied to compa...

Millimeter wave beam alignment (BA) is a challenging problem especially for large number of antennas. Compressed sensing (CS) tools have been exploited due to the sparse nature of such channels. This paper presents a novel deterministic CS approach for BA. Our proposed sensing matrix which has a Kronecker-based structure is sparse, which means it is computationally efficient. We show that our proposed sensing matrix satisfies the restricted isometry property (RIP) condition, which guarantees the reconstruction of the sparse vector. Our approach outperforms existing random beamforming techniques in practical low signal to noise ratio (SNR) scenarios.

In this paper, we are proposing a map-based approach for the optimal placement of multiple UAV-based flying wireless relays in a cellular network. The tackled problem is two-fold, involving a joint UAV-user association problem and 3D placement problem. While related problems were addressed before, the novelty of our approach lies in the fact it builds on a combination of probabilistic and deterministic line-of-sight (LoS) classifiers which exploits the availability of a 3D city map. While the original problem is very challenging in its dimension, we give a low-complexity approach to the placement problem by approximating the optimum UAV positions with a suitably weighted combination of user positions. Our simulations suggest a performance close to that obtained with high complexity exhaustive search for placement.

In this paper, we present and compare three novel model‐cum‐data‐driven channel estimation procedures in a millimeter‐wave Multi‐Input Multi‐Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) wireless communi‐ cation system. The transceivers employ a hybrid analog‐digital architecture. We adapt techniques fromawide range of signal processing methods, such as detection and estimation theories, compressed sensing, and Bayesian inference, to learn the un‐ known virtual beamspace domain dictionary, as well as the delay‐and‐beamspace sparse channel. We train the model‐based algorithmswith a site‐speci ic training dataset generated using a realistic ray tracing‐basedwireless channel simulation tool. We assess the performance of the proposed channel estimation algorithms with the same site’s test data. We benchmark the performance of our novel procedures in terms of normalized mean squared error against an existing fast greedy method and empirically show thatmodel‐based approa...

A beam codebook of 5G millimeter wave (mmWave) for data communication consists of multiple high-peak-gain beams to compensate the high pathloss at the mmWave bands. These beams also have to point to different angular directions, such that by performing beam searching over the codebook, a good mmWave signal coverage over the full sphere around the terminal (spherical coverage) can be achieved. A beam codebook design that assumes ideal omni-directional antenna pattern, and neglects the impact of terminal housing around the antenna, does not work well because the radiation pattern of a practical mmWave antenna combined with the impact of terminal housing is highly irregular. In this paper, we propose a novel and efficient method to generate a beam codebook to boost the spherical coverage of mmWave terminals. The method takes as inputs the measured or simulated electric field response data of each antenna and provides the codebook according to the requirements on the codebook size, spherical coverage, etc. The method can be applied in a straightforward manner to different antenna type, antenna array configuration, placement and terminal housing design. Our simulation results show that the proposed method generates a codebook better than the benchmark and 802.15.3c codebooks in terms of the spherical coverage.

Today’s wireless networks provide us reliable connectivity. However, if a disaster occurs, the whole network could be out of service and people cannot communicate. Using a fast deployable temporally network by mounting small cell base stations on unmanned aerial vehicles (UAVs) could solve the problem. Yet, this raises several challenges. We propose a capacity-deployment tool to design the backhaul network for UAV-aided networks and to evaluate the performance of the backhaul network in a realistic scenario in the city center of Ghent, Belgium. This tool assigns simultaneously resources to the ground users—access network—and to the backhaul network, taking into consideration backhaul capacity and power restrictions. We compare three types of backhaul scenarios using a 3.5 GHz link, 3.5 GHz with carrier aggregation (CA) and the 60 GHz band, considering three different types of drones. The results showed that an optimal UAV flight height (80 m) could satisfy both access and backhaul n...

Semenjak layanan mobile broadband seperti 4G hadir di Indonesia, pertumbuhan layanan data meningkat sangat pesat. Bermacam aplikasi mobile bermunculan. Tidak hanya membutuhkan data rate yang tinggi, aplikasi-aplikasi tersebut juga menuntut latency yang rendah agar dapat berjalan dengan sempurna, contohnya mobile gaming. Kebutuhan akan layanan data tersebut tidak hanya dibutuhkan di kota-kota besar saja, melainkan juga sudah sampai ke pelosok-pelosok negeri. Hal ini dikarenakan penetrasi pengguna internet dan mobile devices kini sudah berkembang pesat. Dikutip dari Websindo.com, per Januari 2019, penetrasi pengguna internet di Indonesia sudah mencapai 56% [1]. Untuk memenuhi kebutuhan tersebut, operator-operator di Indonesia saat ini tengah berlomba-lomba dalam melakukan ekspansi jaringan mobile broadband. Sebagai contoh yaitu Indosat Ooredoo yang pada tahun 2018 memiliki program 4G Overlay yang targetnya yaitu membuat semua BTS miliknya menjadi BTS yang mendukung teknologi 4G [2]. Dari segi infrastruktur telekomunikasi, jaringan transmisi (backhaul / transport network) merupakan hal yang harus diperhatikan oleh para operator ketika ingin melakukan ekspansi 4G (maupun 5G nantinya). Fiber optic adalah solusi terbaik untuk backhaul/transport network di era 4G dan 5G karena menawarkan data rate yang tinggi dan juga latency yang rendah. Namun penetrasi jaringan fiber optic masih belum bisa menjangkau seluruh wilayah, contohnya area rural. Saat ini kebanyakan operator di Indonesia masih mengandalkan teknologi microwave sebagai backhaul transmisinya yang mana kapasitasnya terbatas. Pada makalah ini dibahas mengenai analisis risiko dari proyek ekspansi mobile broadband network operator telekomunikasi di area-area dengan kapasitas transmisi yang terbatas. Definisi dari "area-area dengan kapasitas transmisi yang terbatas" pada makalah ini adalah daerah-daerah rural yang belum terjangkau fiber optic dan masih menggunakan microwave sebagai backhaul access-nya. Dengan kapasitas yang terbatas, risiko terjadinya kepadatan (congestion) di jaringan kemungkinan besar akan sering dijumpai selama proyek berlangsung. Isu congestion ini tidak hanya berdampak pada jalannya proyek saja, melainkan dapat berdampak pula pada performa jaringan eksisting yang sudah ada. Namun dengan analisis risiko yang tepat, dampak dari congestion tersebut bisa diminimalisir sehingga operator dapat tetap bisa terus menjalankan proyek ekspansinya. Output yang diharapkan dari makalah ini adalah bisa menjadi bahan rujukan atau pertimbangan operator-operator telekomunikasi (baik di Indonesia maupun di luar negeri) dalam mengidentifikasi resiko yang mungkin terjadi ketika mencoba untuk melakukan ekspansi mobile broadband network dengan kondisi kapasitas jaringan transmisi yang terbatas.

Keywords—4G, 5G, backhaul, transport, rural, congestion, risk

Wireless backhaul communication has been recently realized with large antennas operating in the millimeter wave (mmWave) frequency band and implementing highly directional beamforming. In this paper, we focus on the alignment problem of narrow beams between fixed position network nodes in mmWave backhaul systems that are subject to small displacements due to wind flow or ground vibration. We consider nodes equipped with antenna arrays that are capable of performing only analog processing and communicate through wireless channels including a line-of-sight component. Aiming at minimizing the time needed to achieve beam alignment, we present an efficient method that capitalizes on the exchange of position information between the nodes to design their beamforming and combining vectors. Some numerical results on the outage probability with the proposed beam alignment method offer useful preliminary insights on the impact of some system and operation parameters.

5G+ systems expect enhancement in data rate and coverage area under limited power constraint. Such requirements can be fulfilled by the densification of small cells (SCs). However, a major challenge is the management of fronthaul links connected with an ultra dense network of SCs. A cost effective and scalable idea of using network flying platforms (NFPs) is employed here, where the NFPs are used as fronthaul hubs that connect the SCs to the core network. The association problem of NFPs and SCs is formulated considering a number of practical constraints such as backhaul data rate limit, maximum supported links and bandwidth by NFPs and quality of service requirement of the system. The network centric case of the system is considered that aims to maximize the number of associated SCs without any biasing, i.e., no preference for high priority SCs. Then, two new efficient greedy algorithms are designed to solve the presented association problem. Numerical results show a favorable performance of our proposed methods in comparison to exhaustive search.