Indo-British Workshop on Biodiversity, held in Various Places in India during 30 January–12 February 1993

In this paper, we study the application of unmanned aerial vehicle (UAV) base stations (BSs) in order to improve the cellular network capacity. We consider flying BSs where BS equipments are mounted on UAVs, making it possible to move BSs freely in space. We study the optimization of UAVs' trajectory in a network with mobile users to improve the system throughput. We consider practical two-hop communications, i.e., the access link between a user and the UAV BS, and the backhaul link between the UAV BS and a macrocell BS plugged into the core network. We propose a reinforcement learning based algorithm to control the UAVs' mobility. Additionally, the proposed algorithm is subject to physical constraints of UAV mobility. Simulation results show that considering both the backhaul and access links in the UAV mobility optimization is highly effective in improving the system performance than only focusing on the access link.

This paper provides the performance characterization of a three-dimensional (3D) two-hop decode-and-forward (DF) aerial-terrestrial communication network, where unmanned aerial vehicles (UAVs) coexist with terrestrial base stations (BSs) to serve a set of user equipment (UE) on the ground. We assume that each UE connects either to a BS via access link or through a UAV to a BS via joint access and backhaul links, where the link from the UE to the UAV is an access link and from the UAV to the BS is a backhaul link. To capture the impact of directionality in practical antennas, we use a model developed by the third generation partnership project (3GPP) for the antenna radiation pattern of both BSs and UAVs. Following the nearest neighbor association policy, we obtain the joint distance and angle distribution of the serving UAV to the origin in a 3D setting using tools from stochastic geometry. Furthermore, we identify and analyze key mathematical constructs as the building blocks of characterizing the received signal-to-interference-plus-noise ratio (SINR) distribution at the typical UE for the DF relaying protocol. Using these intermediate results, we derive an exact mathematical expression for the coverage probability in UAV-assisted two-hop DF cellular networks. One key takeaway from our analysis is the existence of a mean UAV height and a 3D density of UAVs that optimize the network coverage performance.

With the successful demonstration of in-band full-duplex (IBFD) transceivers, a new research dimension has been added to wireless networks. This paper proposes an interesting use case of this capability for IBFD self-backhauling heterogeneous networks (HetNet). IBFD self-backhauling in a HetNet refers to IBFD-enabled small cells backhauling themselves with macro cells over the wireless channel. Owing to their IBFD capability, the small cells simultaneously communicate over the access and backhaul links, using the same frequency band. The idea is doubly advantageous, as it obviates the need for fiber backhauling small cells every hundred meters and allows the access spectrum to be reused for backhauling at no extra cost. This work considers the case of a two-tier cellular network with IBFD-enabled small cells, wirelessly backhauling themselves with conventional macro cells. For clear exposition, the case considered is that of FDD network, where within access and backhaul links, the downlink (DL) and uplink (UL) are frequency duplexed ($f1$, $f2$ respectively), while the total frequency spectrum used at access and backhaul ($f1+f2$) is the same. Analytical expressions for coverage and average downlink (DL) rate in such a network are derived using tools from the field of stochastic geometry. It is shown that DL rate in such networks could be close to double that of a conventional TDD/FDD self-backhauling network, at the expense of reduced coverage due to higher interference in IBFD networks. For the proposed IBFD network, the conflicting aspects of increased interference on one side and high spectral efficiency on the other are captured into a mathematical model. The mathematical model introduces an end-to-end joint analysis of backhaul (or fronthaul) and access links, in contrast to the largely available access-centric studies.

Since the deployment of optical communications networks, carriers have used many mechanisms to protect fiber in the core, because of the large volume of traffic carried in the core, and the affect of a failure on the entire user community. Access links, connecting end users to the core network were not protected because they affected a small number of customers, carried relatively low bandwidth traffic and were less critical. As enterprises use ever growing bandwidth and become increasingly dependent on their network connectivity, they demand protected services. Since fiber breaks can occur anywhere in the network, including the so-called last mile carriers are looking today for protection systems for the access and edge network links. This paper focuses on the emerging solutions for this application, detailing the key criteria for selecting fiber protection switches: optical performance and cost effectiveness (important because the cost must be amortized over a small number of customers). It discusses solutions to the various access network topologies and common protection schemes.

We investigate resource optimization for the downlink cloud small cell network, where the baseband unit pool communicates with the buffer-aided small remote radio heads (SRRHs) through free space optical fronthaul, and SRRHs transmit to the user equipments (UEs) by using time division multiplexing-based millimeter wave access links. Our objective is to maximize the supportable aggregate data arrival rate in the network by exploiting the inter-dependence of fronthaul and access links. Toward this objective, we consider maximum acceptable end-to-end queue-length bound violation probability constraints, load-balancing constraints in the access link, fronthaul link selection constraints, and transmit power budget constraints of fronthaul and access links. Since the joint fronthaul and access link optimization is a non-convex and combinatorial problem, we develop an iterative solution by decomposing the original optimization problem into two sub-problems. The first sub-problem optimally obtains fronthaul and access link power allocation and fronthaul link selection by using Lagrangian dual decomposition and canonical one-to-one matching techniques. By employing the Lagrangian dual decomposition and alternating optimization techniques, the second sub-problem obtains near optimal data arrival rate for each UE, UE-SRRH associations, fronthaul rate allocation among the transmitted data for the UEs, and the transmission duration scheduling in millimeter wave access link. An algorithm of polynomial complexity is developed in order to determine the supportable aggregate data arrival rate by considering the statistical quality-of-service requirements, and its convergence is proved. The simulation results depict that the proposed scheme significantly improves the aggregate data arrival rate over several benchmark schemes.

In this study, the authors adopt the non‐orthogonal multiple access (NOMA) technique to improve the spectrum efficiency in the wireless backhaul networks, whereby the downlink and uplink NOMA techniques are applied for the backhaul and access links, respectively. Due to the coupling between the backhaul and access transmission stages, the transmission power should be carefully allocated in both stages so that the overall throughput can be maximised. They start with the single user equipment (UE) case and consider different scenarios and analyse the tradeoff between the access and backhaul links, and the optimal power allocation solutions are obtained accordingly. They then extend the analysis to the multi‐UE case and formulate the optimal power allocation problem, which is solved using the Lagrangian dual decomposition algorithm. Simulation results demonstrate that the proposed schemes are effective in improving the throughput and outperforms the conventional orthogonal multiple access technique under different network settings.

The cellular Internet of Things (IOT) in its first release which was published in 3GPP Rel.2 has features like longer battery life, low cost of devices, provides additional coverage enhancements. The cellular IOT has additional features of great deal of flexibility like downlink messages, software up gradation in the move and transmission of bigger data. In this context increasing capacity with finite power requirement becomes desirable for achieving the standard system performance, in broadband multimedia services. In this chapter, we introduce a novel approach for optimal resource allocation for Multiple-Input-Multiple-Output (MIMO) system deployed with relay nodes (RNs) for users residing at cell edges. In the proposed model Equal Transmit Power allocation when Channel State Information (CSI) is not known and Adaptive transmit power when CSI is known at transmitter has been used. The resource allocation problem considers the maximization of entropy on the direct link in order to maximize the information rate and hence capacity. The main objective is to allocate the resources to the users optimally for better Quality of services on both access and relay link. The KKT condition has been used for solving classical convex optimization problem on both the links. The optimal values derived prove that proposed allocation result in water filling phenomenon for capacity improvement on both relay and access link.

Relaying is one of the promising approaches for extending service coverage and improving quality of service. The self-backhauling of relays towards a serving (donor) eNode B provides cost-effective solution for deployment scenarios where conventional backhauling is either costly or unavailable. The end-to-end throughputs achievable by users served by relays are dependent on achievable throughputs on both the relay access and backhaul links. The 3GPP standardized Type 1 inband relay node (RN) employs a time-based resource partitioning between relay backhaul and access links. This resource allocation strategy coupled with sharing of eNode B (eNB) resources between the RN and users served directly by the eNB usually creates a backhaul bottleneck. The relay backhaul link performance is further degraded due to intercell interference, particularly on the cell edge where the deployment of relays are usually targeted. In this paper, the relay user's throughput enhancements by relaxation of relay backhaul bottlenecks are investigated through the use of beamforming and interference mitigation techniques. Simulation results demonstrate significant improvements in relay backhaul performance and end-to-end throughputs for relay users through the use of limited feedback beamforming and interference mitigation schemes.

Wavelength converters reduce the connection blocking probability in wavelength-routed networks by eliminating the wavelength continuity constraint. We develop a method for deployment of wavelength converters in wavelength-routed networks with an overlay model. In these networks, most wavelength converters are deployed on edge nodes to cover the difference in the numbers of wavelengths multiplexed on access and core links. Therefore reduction of wavelength converter cost on edge nodes leads to minimizing the wavelength converter cost in the whole network. We propose an ingress edge node architecture with fixed wavelength converters that have limited wavelength convertibility but are more economical than full wavelength converters. In our architecture, each input access link of ingress edge nodes is equipped with fixed wavelength converters, and input wavelengths from the access links are evenly distributed on the output core link. As a result, competition for a free wavelength on an output core link is avoided. Simulation results show that our edge node architecture offers about 20% cost reduction compared with a node architecture that uses only full wavelength converters where networks are actually under operation and a full wavelength converter cost to fixed wavelength converter cost ratio is 3:1.

In 5G ultradense heterogeneous networks, wireless backhaul, as one of the important base station (BS) resources that affect user services, has attracted more and more attention. However, a user would access to the BS which is the nearest for the user based on the conventional user association scheme, which constrains the network performance improvement due to the limited backhaul capacity. In this paper, using backhaul‐aware user association scheme, semiclosed expressions of network performance metrics are derived in ultradense heterogeneous networks, including coverage probability, rate coverage, and network delay. Specifically, all possible access and backhaul links within the user connectable range of BSs and anchor base stations (A‐BSs) are considered to minimize the analytical results of outage probability. The outage for the user occurs only when the access link or backhaul link which forms the link combination with the optimal performance is failure. Furthermore, the theoretical analysis and numerical results evaluate the impact of the fraction of A‐BSs and the BS‐to‐user density ratio on network performance metric to seek for a more reasonable deployment of BSs in the practical scenario. The simulation results show that the coverage probability of backhaul‐aware user association scheme is improved significantly by about 2× compared to that of the conventional user association scheme when backhaul is constrained.

Full-duplex self-backhauling is promising to provide cost-effective and flexible backhaul connectivity for ultra-dense wireless networks, but also poses a great challenge to resource management between the access and backhaul links. In this paper, we propose a user-centric joint access-backhaul transmission framework for full-duplex self-backhauled wireless networks. In the access link, user-centric clustering is adopted so that each user is cooperatively served by multiple small base stations (SBSs). In the backhaul link, user-centric multicast transmission is proposed so that each user’s message is treated as a common message and multicast to its serving SBS cluster. We first formulate an optimization problem to maximize the network weighted sum rate through joint access-backhaul beamforming and SBS clustering when global channel state information (CSI) is available. This problem is efficiently solved via the successive lower-bound maximization approach with a novel approximate objective function and the iterative link removal technique. We then extend the study to the stochastic joint access-backhaul beamforming optimization with partial CSI. Simulation results demonstrate the effectiveness of the proposed algorithms for both full CSI and partial CSI scenarios. They also show that the transmission design with partial CSI can greatly reduce the CSI overhead with little performance degradation.

Light-fidelity (Li-Fi) is an emerging technology for wireless optical networking using the principle of visible light communication (VLC). Li-Fi attocells are smaller in size than the radio frequency (RF) femtocells, suitable for deploying ultradense cellular networks. In this paper, a novel wireless backhaul solution is proposed for indoor Li-Fi attocell networks using VLC, which is already embedded in the Li-Fi base station (BS) units. Since the backhaul links operate in the visible light spectrum, two methods are proposed for bandwidth allocation between the access and backhaul links, namely, full frequency reuse (FR) and in-band (IB). In order to realize dual-hop transmission over the backhaul and access links, both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols are analyzed. Considering a direct current optical orthogonal frequency division multiplexing (DCO-OFDM)-based multiple access system, novel signal-to-interference-plus-noise ratio (SINR) and spectral efficiency expressions are then derived for user equipment (UE) randomly distributed in each attocell. Downlink performance of the optical attocell network is assessed in terms of the average spectral efficiency using Monte Carlo simulations. Guidelines are given for the design of the proposed wireless backhaul system.

Self-backhaul is flexible and cost efficient for ultra dense network (UDN) since it provides backhaul using the same wireless technology as access link. Content prediction and caching can lower the load on backhaul and improve user experience. Therefore, an algorithm named tri-stage fairness (TSF) is proposed to solve the resource allocation problem in UDN with self-backhaul and caching, in which cells without direct network connection (rTP) access core network through donor TP (dTP). In TSF, rTP determines to transmit files cached in rTP (rTP files) or the files not cached in rTP (dTP files) according to delay and link capacity, and allocate access link resource using proportional fairness algorithm. dTP allocates backhaul resource among its users and rTPs with fairness considerations, and decides the time each rTP spends on backhaul link. Fairness, efficiency, overhead and complexity are jointly considered in TSF. To facilitate system level simulation, a traffic model considering the influence of caching is also introduced. Simulation results suggest flexible resource allocation between access and backhaul link yield substantial performance gain.

This paper considers a unmanned aerial vehicle (UAV)-enabled cellular network, in which multiple UAVs are deployed as aerial base stations (BSs) to serve users distributed on the ground. Different from prior works that ignore UAVs’ backhaul connections, we practically consider that these UAVs are connected to the core network through a ground gateway node via rate-limited multi-hop wireless backhauls. We also consider that the air-to-ground (A2G) access links from UAVs to users and the air-to-air (A2A) backhaul links among UAVs are operated over orthogonal frequency bands. Under this setup, we aim to maximize the common (or minimum) throughput among all the ground users in the downlink of this network subject to the flow conservation constraints at the UAVs, by optimizing the UAVs’ deployment locations, jointly with the bandwidth and power allocation of both the access and backhaul links. However, the common throughput maximization is a non-convex optimization problem that is difficult to be solved optimally. To tackle this issue, we use the techniques of alternating optimization and successive convex programming (SCP) to obtain a locally optimal solution. Numerical results show that the proposed design significantly improves the common throughput among all ground users as compared to other benchmark schemes.

Service modes of single access and multiple access for data relay satellite system (DRSS) are presented in this paper. According to independent link resource scheduling for two types of access, rapid response service mode with single access link and multiple access link satellite co-processing is proposed, which using data relay satellite (DRS) multiple access return links panoramic beams as application channel. Users’ access applications could be processed with digital beamforming at the ground center station (GCS) without changing the status of DRS and GCS. Access application can be rapidly responded by scheduling available single access and multiple access link resources with single or several satellites from GCS after request accepted. Users in orbit could achieve real-time or quasi-real-time access by applying online with both random access and rapid access. Rapid response service extends the normal service mode of data relay satellite system. Simulation results show the capability improved by optimization of system resource allocation. And these improve the efficiency and flexibility of service capabilities of DRSS.