This article presents a novel approach to designing millimeter-wave (mmWave) cellular communication systems, based on joint phase time array (JPTA) radio frequency (RF) frontend architecture. JPTA architecture comprises time-delay components appended to conventional phase shifters, which offer extra degrees of freedom to be exploited for designing frequency-selective analog beams. Hence, a mmWave device equipped with JPTA can receive and transmit signals in multiple directions in a single time slot per RF chain, one direction per frequency subband, which alleviates the traditional constraint of one analog beam per transceiver chain per time slot. The utilization of subband-specific analog beams offers a new opportunity in designing mmWave systems, allowing for enhanced cell capacity and reduced pilot overhead. To understand the practical feasibility of JPTA, a few challenges and system design considerations are discussed in relation to the performance and complexity of the JPTA systems. For example, frequency-selective beam gain losses are present for the subband analog beams, e.g., up to 1 dB losses for 2 subband cases, even with the state-of-the-art JPTA delay and phase optimization methods. Despite these side effects, system-level analysis reveals that the JPTA system is capable of improving cell capacity: 5%-tile cell throughput by up to 65%. To the best of the authors' knowledge, this article is the first to explain the system-level benefits and system-design challenges of JPTA, with an analysis of the performance tradeoff based on an intuitive metric of beam gain losses.

High-frequency wideband cellular communications over mmWave and sub-THz offer the opportunity for high data rates. However, it also presents high path loss, resulting in limited coverage. High-gain beamforming from the antenna array is essential to mitigate the coverage limitations. The conventional phased antenna arrays (PAA) cause high scheduling latency owing to analog beam constraints, i.e., only one frequency-flat beam is generated. Recently introduced joint phase-time array (JPTA) architecture, which utilizes both true-time-delay (TTD) units and phase shifters (PSs), alleviates analog beam constraints by creating multiple frequency-dependent beams for scheduling multiple users at different directions in a frequency-division manner. One class of previous studies offered solutions with "rainbow" beams, which tend to allocate a small bandwidth per beam direction. Another class focused on uniform linear array (ULA) antenna architecture, whose frequency-dependent beams were designed along a single axis of either azimuth or elevation direction. This paper presents a novel 3D beamforming design that maximizes beamforming gain toward desired azimuth and elevation directions and across sub-bands partitioned according to scheduled users’ bandwidth requirements. We provide analytical solutions and iterative algorithms to design the PSs and TTD units for a desired subband beam pattern. Through simulations of the beamforming gain, we observe that our proposed solutions outperform the state-of-the-art solutions reported elsewhere.

Joint phase-time arrays (JPTA) is a new mmWave radio frequency front-end architecture constructed with appending time-delay elements to phase shifters for analog beamforming. JPTA allows the mmWave base station (BS) to form multiple frequency-dependent beams with a single RF chain, exploiting the extra degrees of freedom the time-delay elements offer. Without requiring extra power-hungry RF chains, a BS with JPTA can schedule multiple users in different directions in a frequency-division multiplexing (FDM) manner. A BS with JPTA achieves various advantages over the traditional analog beamforming system. Simulation results show that JPTA can bring significant system-level benefits, e.g., extending uplink throughput coverage by 100%. To realize these system benefits of JPTA, high-resolution delay elements with a wide delay dynamic range are essential. With newly developed delay elements, we demonstrate that a single TRX RF chain can serve four users in four different directions in the mmWave band.

This chapter generalizes the downlink results to the case of a heterogeneous cellular network (HetNet), where different classes of base-stations are present in the network. Deploying small cells overlaid on an existing wide area macrocell network is a key direction in ongoing and future cellular network deployments, so this is an important but nontrivial generalization, and one that has gained considerable popularity for the stochastic geometric approach. Overall, the outlook for densification with small cells is quite bright in light of the results of Chap. 4.

This chapter summarizes the downlink model and methodology to computing the coverage probability (SINRccdf), which are amongst the most tractable and fundamental results in stochastic geometry as applied to wireless communication. In JGA’s course, which includes many other topics and is just meant to provide an introduction to stochastic geometry, it is often not feasible to go much further than the results in this chapter. There have been some recent advances in the downlink analysis of the so-called typical cell, which are also included in this chapter.

This chapter asks the question, “is there a limit to how much density a cellular network can tolerate?” We show that the answer to that question is “yes”, and the precise answer of “how much” hinges on the path loss model in particular, as well as several other network parameters. In particular, the path loss model should change for short range communications, and the improved propagation paradoxically decreases the network throughput once a certain density is reached. Overall, this chapter provides a more sobering view of densification than the preceding one and shows the importance of revisiting models and analyses in the light of new information and circumstances.

This book features an approachable introduction to the analysis of cellular networks as well as stochastic geometry as applied to cellular networks.

This chapter provides a concise background on the key tools used in the subsequent chapters, which includes the most essential stochastic geometry Definitions and Theorems. The authors also recommend full length texts focusing on stochastic geometry for wireless networks, such as [6], [7], [8], for a more comprehensive and deeper treatment, including [9] which is focused on cellular networks specifically.

This chapter focuses on an uplink cellular system model including transmit power control at the mobile user (i.e., handset). This problem is more difficult than the downlink due to the coupling between the handset point process and the BS point process when it is assumed (realistically) that only a single handset can be active per cell (in a given time/frequency resource). Using some recent results, this chapter carefully models this coupling and provides a comprehensive treatment of uplink coverage.

In this paper, we establish the potential of joint phase-time arrays (JPTAs) for uplink coverage extension in cellular systems. JPTA allows the base station (BS) to create frequency-dependent wide-beams without sacrificing the array gain. In this work, we propose a novel use case of JPTA where the BS exploits the frequency-dependent beams to serve multiple users’ equipment (UEs) at different directions simultaneously with the full array gain and with no inter-UE interference. This is achieved by assigning each UE a corresponding bundle of sub-carriers that benefit from the full array-gain. A key feature of this scheme is the prolonged channel access for uplink communication for each user, due to the BS’s ability to serve multiple UEs at the same time. We focus on two performance metrics: uplink coverage and uplink throughput. Our results show that using JPTA can extend the uplink coverage range by $3\times $ while boosting the uplink throughput by providing more flexibility for the BS in resource allocation. These results are based on both theoretical analysis and 3GPP spec-compliant simulations with a sub-terahertz transceiver prototype.

Hybrid beamforming is an attractive solution to build cost-effective and energy-efficient transceivers for millimeter-wave and terahertz systems.However, conventional hybrid beamforming techniques rely on analog components that generate a frequency flat response such as phase-shifters and switches, which limits the flexibility of the achievable beam patterns.As a novel alternative, this paper proposes a new class of hybrid beamforming called Joint phase-time arrays (JPTA), that additionally use true-time delay elements in the analog beamforming to create frequency-dependent analog beams.Using as an example two important frequency-dependent beam behaviors, the numerous benefits of such flexibility are exemplified.Subsequently, the JPTA beamformer design problem to generate any desired beam behavior is formulated and nearoptimal algorithms to the problem are proposed.Simulations show that the proposed algorithms can outperform heuristics solutions for JPTA beamformer update.Furthermore, it is shown that JPTA can achieve the two exemplified beam behaviors with one radio-frequency chain, while conventional hybrid beamforming requires the radio-frequency chains to scale with the number of antennas to achieve similar performance.Finally, a wide range of problems to further tap into the potential of JPTA are also listed as future directions.

In cellular systems, the user equipment (UE) can request a change in the frequency band when its rate drops below a threshold on the current band. The UE is then instructed by the base station (BS) to measure the quality of candidate bands, which requires a measurement gap in the data transmission, thus lowering the data rate. We propose an online-learning based band switching approach that does not require any measurement gap. Our proposed classifier-based band switching policy instead exploits spatial and spectral correlation between radio frequency signals in different bands based on knowledge of the UE location. We focus on switching between a lower (e.g., 3.5 GHz) band and a millimeter wave band (e.g., 28 GHz), and design and evaluate two classification models that are trained on a ray-tracing dataset. A key insight is that measurement gaps are overkill, in that only the relative order of the bands is necessary for band selection, rather than a full channel estimate. Our proposed machine learning-based policies achieve roughly 30% improvement in mean effective rates over those of the industry standard policy, while achieving misclassification errors well below 0.5% and maintaining resilience against blockage uncertainty.

We study the scaling laws of the signal-to-interference-plus-noise ratio (SINR) and the area spectral efficiency ( ASE) in multi-antenna cellular networks, w here the number of antennas scales with the base station (BS) spatial density λ, under the assumption of independent and identically distributed (i.i.d.) channels. We start with the MISO case with N t (λ) transmit antennas and a single receive antenna and prove that the average SINR scales as Nt(λ) /λ and the average ASE scales as λ log (1 + Nt(λ) /λ). For the MIMO case with single-stream eigenbeamforming and N r (λ) ≤ N t (λ) receive antennas, we prove that the scaling laws of the conditional SINR and ASE are agnostic to N r (λ) and scale exactly the same as the MISO case. Hence, deploying multi-antenna BSs can help maintain nonzero per-user throughput and a corresponding linear increase in the ASE in dense cellular networks.

We study how dense multi-antenna millimeter wave (mmWave) cellular network performance scales in terms of the base station (BS) spatial density λ, by studying the signal-to-interference-plus-noise ratio (SINR) and the area spectral efficiency (ASE). If the number of antennas at each BS scales at least linearly with λ, which increases the number of possible beam configurations and their main-lobe gain, and decreases their side-lobe gain, we prove that the SINR approaches a finite random variable that is independent of λ and the ASE scales at least linearly with λ. In contrast, if the number of antennas scales sub-linearly with λ, then the SINR decays to zero and the ASE saturates to a constant. Thus, by moving to higher carrier frequencies with successively smaller antennas, and exploiting the correspondingly increased directionality, cellular operators can in principle avoid the densification plateau (or collapse) in cellular networks and instead continue to harvest linear sum throughput gains through BS densification.

We study the scaling laws of the signal-to-interference-plus-noise ratio (SINR) and area spectral efficiency (ASE) in multi-antenna cellular networks, where the number of antennas scales with the base station (BS) spatial density $\lambda$. We start with the MISO case having $N_t(\lambda)$ transmit antennas and a single receive antenna and prove that the average SINR scales as $\frac{N_t(\lambda)}{\lambda}$ and the average ASE scales as $\lambda\log\left(1+\frac{N_t(\lambda)}{\lambda}\right)$. For the MIMO case with single-stream eigenbeamforming and $N_r(\lambda) \leq N_t(\lambda)$ receive antennas, we prove that the scaling laws of the conditional SINR and ASE are exactly the same as the MISO case, i.e. not dependent on $N_r(\lambda)$. We also show that coordinated beamforming amongst $K\leq N_t(\lambda)$ neighboring BSs does not improve the scaling laws regardless of $K$. From a system design perspective, our results suggest that deploying multi-antenna BSs can help maintain the per-user throughput and the linear increase in the ASE with BS density, while the number of antennas at the user equipment and the use of BS cooperation do not matter much.

We characterize the stability, metastability, and the stationary regime of traffic dynamics in a single-cell uplink wireless system. The traffic is represented in terms of spatial birth-death processes, in which users arrive as a Poisson point process in time and space, each with a file to transmit to the base station. The service rate of each user is based on its signal to interference plus noise ratio, where the interference is from other active users in the cell. Once the file is fully transmitted, the user leaves the cell. We derive the necessary and sufficient condition for network stability, which is independent of the specific bounded path loss function. A novel observation is that for a certain range of arrival rates, the network appears stable for a possibly long time, and then suddenly exhibits instability. This property, which is known in statistical physics but rarely observed in wireless communication, is called metastability. Finally, we propose two heuristic characterizations based on mean-field interpretation, of the network steady-state regime when it exists. The first-order approximation is very simple to compute, but loose in some regimes, whereas the second-order approximation is more sophisticated but tight for the whole range of arrival rates.

This paper studies the effect of the user hand grip on the design of beamforming codebooks for 5G millimeter-wave (mmWave) mobile handsets. The high-frequency structure simulator (HFSS) is used to characterize the radiation fields for fourteen possible handgrip profiles based on experiments we conducted. The loss from hand blockage on the antenna gains can be up to 20 25 dB, which implies that the possible hand grip profiles need to be taken into account while designing beam codebooks. Specifically, we consider three different codebook adaption schemes: a grip-aware scheme, where perfect knowledge of the hand grip is available; a semi-aware scheme, where just the application (voice call, messaging, etc.) and the orientation of the mobile handset is known; and a grip-agnostic scheme, where the codebook ignores hand blockage. Our results show that the ideal grip-aware scheme can provide more than 50% gain in terms of the spherical coverage over the agnostic scheme, depending on the grip and orientation. Encouragingly, the more practical semi-aware scheme we propose provides performance approaching the fully grip-aware scheme. Overall, we demonstrate that 5G mmWave handsets are different from pre-5G handsets: the user grip needs to be explicitly factored into the codebook design.

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 model-based 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 data-driven 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, and so on. 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.

This paper contributes a comprehensive study on the effect of the user hand grip on the design of 5G millimeter-wave (mmWave) mobile handsets, specifically in terms of the antenna module placement and the beamforming codebook. The high-frequency structure simulator (HFSS) is used to characterize the radiation fields for different antenna placements and 14 possible handgrip profiles based on the experiments that we conducted. The loss from hand blockage on the antenna gains can be up to 20-25 dB, which implies that the possible hand grip profiles need to be taken into account while designing the antenna module placement and beamforming codebook. Specifically, we consider three different codebook adaption schemes: a grip-aware scheme, where perfect knowledge of the hand grip is available; a semi-aware scheme, where just the application (voice call, messaging, and so on) and the orientation of the mobile handset is known; and a grip-agnostic scheme, where the codebook ignores the hand blockage. Our results show that the ideal grip-aware scheme can provide more than 50% gain in terms of the spherical coverage over the agnostic scheme, depending on the grip and orientation. Encouragingly, the more practical semi-aware scheme that we propose provides performance approaching the fully grip-aware scheme. Overall, we demonstrate that the 5G mmWave handsets are different from pre-5G handsets: the user grip needs to be explicitly factored into the antenna placement and the codebook design.