Cooperative Beamforming With Nonlinear Power Amplifiers: A Deep Learning Approach for Distributed Networks

Heterogeneous Networks (HetNets) have gained the attraction of the communication industry recently, due to their promising ability to enhance the performance of future broadband Fifth Generation (5G) networks and are integral parts of 5G systems. They can be viewed in multi-dimensional space where, each slice represents a unique tier that has its own Base Station (BS)s and User Equipment (UE)s. Different tiers cooperate with each other for their mutual benefit. Data can be interactively exchanged among the tiers, and UEs have the flexibility to switch between the tiers. The cells in such a heterogeneous cellular networks have variable sizes, shapes, and coverage regions. However, in HetNets with ultra dense BSs, the distance between them gets very small and, they suffer from very high levels of mutual interference. To improve the performance of HetNets, we have done multiple contributions in this dissertation. First, we have developed analytical derivations for optimizing pilot sequence length which is a very crucial factor in acquiring the Channel State Information (CSI) and the channel estimation process in general. Poisson Point Process (PPP) has been widely used to allocate BSs among various tiers so far. However, BS locations obtained using PPP approach may not be optimum to reduce interference. Therefore, in this dissertation, BSs locations are optimized to reduce the interference and improve the coverage and received signal power. Also, we have derived expressions for static UEs coverage probability and network energy efficiency in HetNets. A proper UE association algorithm for HetNets is a great challenge. The classic max-Signal to Interference and Noise Ratio (SINR) or max-received signal strength (RSS) user association algorithms are inappropriate solutions for HetNets as UEs in this context will tend to connect to the Macro BS, which is the one with the highest signal power. A severe load imbalance and significant inefficiency arises and impacts the performance. The aforementioned algorithms tend to associate UEs to BSs with the best received signal power or signal quality. In HetNets, usually Macro BSs are the ones transmitting the strongest signals; hence most UEs tend to associate with the Macro BS leaving Micro BSs with less load. Also, the conventional max-SINR and max-RSS algorithms do not provide adequate results in multi-tier systems. We suggest two centralized algorithms, LSTD and RTLB, for an even UE association to provide fair load distribution. However RTLB outperforms LSTD in real time scenarios as it easily and quickly adapts to rapid network changes. Furthermore, we consider the mobility of nodes. We derive coverage probability for moving UEs considering both handover and no handover scenarios. Proposed algorithms are fast enough to associate the moving users to different Micro and Macro BSs appropriately in real time. Our algorithms are proved to be feasible and provide a path towards attainable future communication systems.

Power amplifier (PA) nonlinearity plays a crucial role in determining the performance of radio frequency (RF) communication systems. Specifically, PA nonlinearity causes the amplitude-phase modulation (APM) constellation points to get distorted, which results in performance degradation. In this paper, we study the effect of PA nonlinearity on the bit error performance of spatial modulation MIMO (SM-MIMO) systems. When the PA distortion parameters are perfectly known at the receiver, the optimal detection rule is the one which minimizes the maximum-likelihood (ML) cost over the distorted constellation. For the case when the receiver has no knowledge of PA distortion parameters, we propose a receiver compensation technique which involves estimating the points of the distorted APM constellation based on training and performing detection using the estimated constellation. Simulation results show that, for SM-MIMO with 16-QAM, the proposed scheme achieves almost the same bit error performance as that achieved using the perfect knowledge of the PA parameters. Also, the proposed scheme is found to perform within 2–4 dB of the performance achieved using an ideal (linear) PA even at low values of input backoff.

Multiple-input multiple-output (MIMO) millimeter-wave (mm-wave) systems are vulnerable to hardware impairments due to operating at high frequencies and employing a large number of radio-frequency hardware components. In particular, nonlinear power amplifiers (PAs) employed at the transmitter distort the signal when operated close to saturation due to energy efficiency considerations. In this paper, we study the performance of an MIMO mm-wave hybrid beamforming scheme in the presence of nonlinear PAs. First, we develop a statistical model for the transmitted signal in such systems and show that the spatial direction of the inband distortion is shaped by the beamforming filter. This suggests that even in the large antenna regime, where narrow beams can be steered toward the receiver, the impact of nonlinear PAs should not be ignored. Then, by employing a realistic power consumption model for the PAs, we investigate the tradeoff between spectral and energy efficiency in such systems. Our results show that increasing the transmit power level when the number of transmit antennas grows large can be counter-effective in terms of energy efficiency. Furthermore, using numerical simulation, we show that when the transmit power is large, analog beamforming leads to higher spectral and energy efficiency compared to digital and hybrid beamforming schemes.

Joint waveform and beamforming design is demonstrated as an effective approach to improve the wireless energy transfer (WET) performance. Meanwhile, the emerging technique of reconfigurable holographic surface (RHS) without the half-wavelength limitation is able to achieve a higher spatial gain. Hence, the RHS-assisted WET system is designed to enhance WET performance by optimizing the waveform and beamforming. However, the ideal linear power amplifier is always conceived, while the nonlinearity of the power amplifier is ignored. In this paper, a more practical nonlinear power amplifier (NPA)-based RHS-assisted WET system is proposed, where the energy harvesting (EH) model by considering the channel aging effect is derived to adapt to the time-varying channel. In order to improve the WET performance, a predistortion technique is adopted to tackle the nonlinear input-output characteristic of NPAs, while the waveform and beamforming are jointly optimized. Simulation results demonstrate that the RHS outperforms the phased array benchmark having the same size on the WET performance, when the NPAs work in the unsaturated region. Furthermore, the impact of the NPAs on the WET performance by considering channel aging effect is demonstrated, while the waveform design is invalid when the NPAs work near the saturation region.

User association is a crucial factor that affects the performance of wireless networks. In current cellular networks, user association is typically coupled, which means an user equipment (UE) must associate with the same base station (BS) in uplink (UL) and downlink (DL). For single-tier wireless networks, such mechanism is simple and effective. However, in heterogeneous ultra-dense networks (UDNs), there are distinct differences in transmission power, data traffic and channel quality etc., for which coupled association could restrict the performance of system. To cope with it, the concept of decoupled UL-DL (DUDe) association has been introduced recently, which enables a UE to associate with different BSs in UL and DL. In this paper, we investigate decoupled UL-DL user association in UDNs. Considering the existence of asymmetric information (i.e., channel gains and intercell interferences), which can be seen as the private information for UE, we propose a contract-theoretic user association approach. Particularly, we model the decoupled association process as a monopoly labor market, where BSs act as employers and offer contracts to employees (i.e., UEs). The contract items cover the available associated bandwidths, transmitted powers and corresponding prices. Then BS broadcasts these drafted contract information, and UE selects to sign the optimal contract by considering her own demands. Numerical results show significant superiorities of DUDe than coupled UL-DL association in perspective of nodes utilities and social surplus, and compared with the existing user association methods, contract-theoretic approach shows a certain improvement in performance.

Symbiotic radio (SR) is a promising technology to support ultralow-power or even zero-power Internet of Things (IoT) devices in the sixth-generation mobile networks. In this article, we propose an energy-aware symbiotic transmission in a reconfigurable intelligent surface (RIS) enhanced SR system, in which an IoT network embeds its own data passively over cellular downlink signals by backscattering. The base station (BS) serves multiple cellular users (CUs) through time division multiple access (TDMA) and each IoT device is associated with one CU. We formulate the BS’s energy minimization problem subject to the constraints of the minimum amounts of transmission bits required by IoT devices and CUs. The user association, the active transmit beamforming at the BS, the passive reflecting beamforming at the RIS, and the frame division policy are jointly optimized. The formulated problem is a mixed integer nonlinear programming (MINLP) problem, which is NP-hard and nonconvex. We decouple the problem and solve the subproblems alternatively. First, we design a many-to-one swap-matching-based algorithm to solve the user association subproblem. Then, we develop a joint cooperative beamforming and time allocation optimization algorithm based on the alternative optimization (AO) and semidefinite relaxation (SDR) techniques. Simulation results show that the proposed joint user association and cooperative beamforming algorithm brings significant performance gain in reducing the energy consumption of the BS with fast convergence speed compared with other schemes.

In cellular systems, BSs (base stations) are ideally desired to be located in the center of cells, but it is sometimes impossible because of the physical and/or social restrictions on the BS setting space. This paper considers the influence of the displacement of the BS location on BS cooperation (BSC) scheme in MIMO (multiple input multiple output) cellular system. For this aim, BS locations are given on fixed points of circles with different radius and rotation angle. The performances of transmission algorithms with and without BSC are quantitatively evaluated under several typical BS locations through computer simulations. The results show the BS location has certain impact, but the BSC is still effective under the BS displacement.

The line-of-sight (LoS) dominant air-ground channels have posed critical interference issues in cellular-connected unmanned aerial vehicle (UAV) communications. In this paper, we propose a new base station (BS) cooperative beamforming (CB) technique for the cellular downlink to mitigate the strong interference caused by the co-channel terrestrial transmissions to the UAV. Besides the conventional CB by cooperatively transmitting the UAV's message, the serving BSs of the UAV exploit a novel CB-based {\it \textbf{interference transmission}} scheme to effectively suppress the terrestrial interference to the UAV. Specifically, the co-channel terrestrial users' messages are shared with the UAV's serving BSs and transmitted via CB so as to cancel their resultant interference at the UAV receiver. To optimally balance between the CB gains for UAV signal enhancement and terrestrial interference cancellation, we formulate a new problem to maximize the UAV's receive signal-to-interference- plus-noise ratio (SINR) by jointly optimizing the power allocations at all of its serving BSs for transmitting the UAV's and co-channel terrestrial users' messages. First, we derive the closed-form optimal solution to this problem in the special case of one serving BS for the UAV and draw useful insights. Then, we propose an algorithm to solve the problem optimally in the general case. Simulation results show that the proposed CB scheme with interference transmission and cancellation (ITC) significantly improves the UAV's downlink SINR as compared to the conventional CB without applying ITC.

The growing complexity of heterogeneous cellular networks (HetNets) has necessitated the need to consider variety of user and base station (BS) configurations for realistic performance evaluation and system design. This is directly reflected in the HetNet simulation models considered by standardization bodies, such as the third generation partnership project (3GPP). Complementary to these simulation models, stochastic geometry-based approach modeling the user and BS locations as independent and homogeneous Poisson point processes (PPPs) has gained prominence in the past few years. Despite its success in revealing useful insights, this PPP-based model is not rich enough to capture all the spatial configurations that appear in real-world HetNet deployments (on which 3GPP simulation models are based). In this paper, we bridge the gap between the 3GPP simulation models and the popular PPP-based analytical model by developing a new unified HetNet model in which a fraction of users and some BS tiers are modeled as Poisson cluster processes (PCPs). This model captures both non-uniformity and coupling in the BS and user locations. For this setup, we derive exact expression for downlink coverage probability under maximum signal-to-interference ratio (SIR) cell association model. As intermediate results, we define and evaluate sum-product functionals for PPP and PCP. Special instances of the proposed model are shown to closely resemble different configurations considered in 3GPP HetNet models. Our results concretely demonstrate that the performance trends are highly sensitive to the assumptions made on the user and SBS configurations.

This paper presents a detailed analysis of the impact of power amplifier (PA) non-linearity on the performance of single carrier (SC) and OFDM systems in 60 GHz spectrum. The efficiency of the considered systems was analyzed by estimating values of the power amplifier output backoff needed to meet the requirements on the transmit spectrum mask (TSM) compliance and error vector magnitude (EVM). Different models of the PA including an experimentally measured model for the 60 GHz PA were considered. It was estimated that for many types of modulations and PA models, SC system can have up to 1.5 dB higher output power than OFDM system. However, for the experimental PA model accounting for amplitude modulation-phase modulation distortion in addition to amplitude modulation amplitude modulation distortion, the difference between the OFDM and SC output power levels was minimal, and OFDM even had approximately 1 dB better performance than SC for the BPSK modulation. A potential improvement in the transmit power due to application of digital predistortion techniques was estimated for both systems to be in the range from 1.5 to 3.4 dB.

This paper analyzes the problem of optimum user association and sum rate maximization for software defined radio access networks (SD-RANs) with access node diversity for fifth generation (5G) wireless networks. We consider four complementary types of access nodes namely, a massive multiple- input multiple-output (MIMO) base station (BS), MIMO BSs, small cells (SCs), and indoor and outdoor distributed antenna systems (DAS). The SDRAN user association problem is solved through a novel three-stage optimization scheme called the place coverage (TPC). TPC divides the user equipment (UEs) into two sets of indoor and outdoor UEs. Initially, TPC associates indoor UEs with the indoor DAS access nodes. Next, outdoor UEs are associated with the outdoor DAS access nodes, SCs, MIMO BSs, and the massive MIMO BS. Finally, the remaining resources of indoor and outdoor access nodes are used to serve the UEs that have not been served. The scope of TPC is multifold. First, TPC reflects the closest model to a real-world diverse 5G network. Secondly, servicing the indoor UEs with iDAS antennas results in lower power load per user for the access network resulting in better coverage, quality, and data speed. Thirdly, TPC provides reduced radiation levels for indoor UEs. Numerical results show that TPC provides significant sum rate and fairness gains over the received signals strength (RSS) based association schemes [1]. Moreover, TPC provides comparable performance levels as the optimum association scheme based on exhaustive search while bringing significant complexity reduction.

Coverage probability of uplink millimeter wave cellular network with non-homogeneous interferers’ point process

Future-generation radio access networks (RAN) are projected to fulfill the diverse requirements of user equipment (UE) by adopting a heterogeneous network (HetNet) environment. Necessary integration of different radio access technologies (RAT), such as 2G, 3G, 4G, wireless local area network (WLAN), and visible light communication (VLC) is inevitable. Moreover, UEs equipped with diverse requirements will be capable of accessing some or all the RATs. The complex HetNet environment with diverse requirements of UEs will present many challenges. The HetNet is likely to suffer severely from load imbalance among the base stations (BSs) from inheriting the traditional user association scheme such as max-SINR (signal-to-interference-plus-noise ratio)/max-RSSI (received signal strength indicator), unless some sophisticated schemes are invented. In this paper, a novel scheme is devised for a joint-user association for load balancing, where BSs are densely deployed and UEs typically have a certain degree of mobility. Unlike most of the present works, a dynamic network is considered where the position and channel condition of the UEs are not fixed. We develop two complex and distributed association schemes based on probability and d-choices, while carefully considering both loads of the BSs and SINR experienced by the UEs. Numerical results validate the efficiency of the proposed schemes by showing a received data-rate fairness among UEs and an improvement in the UE’s minimum received data rate.

With the proliferation of smart devices, machine-to-machine communication, and wearable, data and traffic is increasing enormously. Ultra-densification has been considered a promising technique to achieve substantial advantages in capacity, data rate, and coverage. However, the extensive deployment of devices to support huge data traffic results in high interference and energy issues. This is due to the unplanned deployment of small cells with varying power and coverage. Due to small coverage, users will frequently be changing associations with the base station. In this regard, user association plays a critical role in interference management, load balancing, energy consumption, and spectral efficiency. This paper proposes an energy-efficient load-aware user association technique, which assists the user equipment in selecting an optimal base station. The proposed technique leads to a stable user association considering load (traffic) while improving energy efficiency. The proposed user association operation ends when all user equipment gets associated with base stations by achieving the equilibrium state. Simulation results show that the proposed user association scheme outperforms significantly in load balancing, sum rate, and energy efficiency compared to max-SINR based user association.

We study the user association and scheduling problem in multi-cell multi-user multiple-input multiple-output systems with dynamic traffic. Two successive linear beamforming schemes, namely, zero forcing-successive interference cancellation and adaptive orthogonal beamforming, are adopted in the uplink channel and the downlink channel, respectively. The confidence level of signal-to-interference-plus-noise ratio of a random user is analyzed, in order for base stations (BSs) to decide on the maximum number of active users while guaranteeing the worst-case quality of service. We also derive the conditional expected rate of a random user knowing its local channel state information, in order for users to evaluate the performance and select the BS. Noticing that the performance can be divided into different classes, we model the user association and scheduling problem as an auction game. The auction is equipped with a strategy-proof pricing scheme and can be conducted in a distributed fashion with a limited information exchange. Shown by the simulation, the proposed mechanism has the dominant performance in respect of social welfare, throughput, and load balancing.