Inband D2D Communication for mmwave 5G Cellular Networks

Transcription

1 Inband D2D Communication for mmwave 5G Cellular Networks Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Electronics and Communication Engineering by Research by Gadiraju Divija Swetha International Institute of Information Technology Hyderabad , INDIA March 2018

2 Copyright Gadiraju Divija Swetha, 2018 All Rights Reserved

3 International Institute of Information Technology Hyderabad, India CERTIFICATE It is certified that the work contained in this thesis, titled Inband D2D Communication for mmwave 5G Cellular Networks by Gadiraju Divija Swetha, has been carried out under my supervision and is not submitted elsewhere for a degree. Date Adviser: Dr. Garimella Rama Murthy

4 Dedicated to my parents

5 Acknowledgments The successful outcome of this thesis required a lot of support and encouragement from many people. I am fortunate to have the guidance and assistance till the completion of my MS thesis work. I extend my gratitude to all of them. First and the foremost I want to thank my advisor Dr. Garimella Rama Murthy for accepting me as a student under his guidance and for considering my research interests. Without his valuable guidance and support this work would not have been possible. I am thankful to all my friends and well wishers for their constant encouragement and their helpfulness. I am fortunate to get the assistance from my friends. I thank all my fellow MS friends for their encouragement. Also, I would like to extend my sincere regards to all my colleagues and lab members. Above all, my parents have supported me and had faith in me even in the toughest phase. I express my deepest gratitude for providing me with unfailing support and continuous encouragement throughout my years of study. Finally, I dedicate this thesis to my parents for their unconditional love. v

6 Abstract The cellular users demand has increased drastically with the emergence of mobile internet technologies. In order to satisfy the demand, cellular service providers have improved each generation of cellular networks over its predecessors. However, the fifth generation (5G) cellular technologies would revolutionize the network architecture and would go beyond the trend of previous generations. Device-to-Device (D2D) communication is one such revolutionary technology in which the mobile users communicate with each other directly without traversing the base station. D2D communication is actively studied with special focus on public safety in 3GPP. D2D communication with network control has many other use-cases. Also, the 5G cellular technology includes millimeter wave (mmwave) for communication. Along with massive bandwidth availability at mmwave frequencies, the advantage of extensive frequency reuse and directive propagation is gained. The integration of device-to-device (D2D) and mmwave technology would improve the system performance and spectral efficiency to a great extent. Moreover, with the emerging trends in Internet-of-Things (IoT), massive device connectivity is required with high connection speed. Hence, D2D communication technology plays a vital role in maintaining Quality of Service (QoS) in IoT applications. The thesis studies D2D communication in inband mode where the resources of the licensed spectrum are used for communication. The work emphasizes on the system performance improvement because of the integration of mmwave technology and D2D communication. Underlay mode D2D communication, where the devices reuse the resources of a cellular user, is analyzed. The problems of resource allocation and interference avoidance are addressed. Then, the importance of fairness in resource allocation and the power allocation are studied. An approach for resource allocation and power allocation is proposed which is adaptive to traffic demand. Results show that the proposed scheme can significantly enhance the system performance in terms of fairness and spectral efficiency. Inband D2D communication with selective operation in underlay and overlay modes aiming to maximize QoS is explored. Spectrum underutilization is the key challenge in overlay mode which is addressed in this work. In areas with high call traffic density, D2D communication can operate in overlay mode because of its low complexity as resources are dedicated and the absence of interference with cellular users. In order to maximize spectrum utility, resources are dynamically assigned to overlay mode based on traffic demand. System performance in overlay mode is analyzed. A dynamic mode selection scenario is considered while addressing resource vi

7 vii allocation, power control and interference avoidance. Thus, formulated problem is solved using a single heuristic algorithm for resource management in both the modes. Performance of the proposed algorithm is evaluated through simulations. The proposed scheme has optimal performance for a dense 5G network in controlled underlay and overlay operations and overcomes the problem of spectrum wastage in overlay mode by its selective operation.

8 Contents Chapter Page 1 Introduction Introduction and Motivation Next Generation Wireless Technologies Millimeter Wave Technology D2D Communication Comparison between Traditional Communication and D2D Communication Taxonomy Inband D2D communication Outband D2D communication Integration of D2D Communication and mmwave Technology Thesis Contributions Thesis Organization D2D Communication as an Underlay to 5G Cellular Systems System Model Channel Model Problem Description Achievable Data Rate and Problem Formulation Algorithm for Resource Management Performance Evaluation Summary Fair Resource Allocation and Power Allocation Method for Underlay D2D Communication Background System Model Channel Model Spectrum Resource and Power Allocation Problem Description and Formulation Suboptimal Algorithm Performance Evaluation Summary Inband D2D Communication Operating in Underlay and Overlay Modes Selectively Background System Model viii

9 CONTENTS ix Mode Selection Channel Model and Achievable Data Rate Problem Formulation 1: Assignment of Dedicated Resources to Overlay Mode Proposed Mechanism and Simulation Problem Formulation 2: Resource Allocation for Inband D2D communication Problem Description for Underlay Mode Problem Description for Overlay Mode Problem Formulation Proposed Algorithm Performance Evaluation of Proposed Algorithm Simulation Settings Simulation Results Summary Conclusion and Future Work Conclusion of Thesis Achievements Future Research Directions Bibliography

10 List of Figures Figure Page 1.1 Millimeter wave spectrum [5] Illustration of benefits and use cases of D2D communication [26] Classification of D2D communication Schematic representation of inband overlay, inband underlay, and outband D2D communication [6] System model for multiple underlay D2D communications in a cell illustrating interference between D k,u k, D 3, U b2 and D b Throughput for varying transmission power and with fixed L Throughput for varying number of D2D users and with fixed transmission power System model with network controlled D2D communications in a cell Evaluation of spectral efficiency for proposed scheme Fairness comparison between the proposed scheme and fixed power allocation System model with multiple inband D2D connections (both underlay and overlay modes) in a cell and illustrating interference between D2D users Optimum number of RB assignment at different instants of time for varying call traffic density System throughput for varying distance between D2D pair and with fixed N d Underlay D2D users throughput variation for different number of cellular users, N c D2D throughput comparison of D2D users in underlay and overlay mode, varying the number of D2D pairs Throughput comparison in underlay and overlay mode, varying the total number of users x

11 List of Tables Table Page 2.1 Simulation Parameters for Algorithm Simulation Parameters for Algorithm Simulation Parameters for Algorithm xi

12 List of Abbreviations 4G OFDM MIMO 5G mmwave D2D UE BS IoT DCA LOS NLOS ISI MAC HetNet V2V M2M QoS LTE CSI RB SINR AWGN SUWF NLP MINLIP Fourth Generation Orthogonal Frequency Division Multiplexing Multiple Input Multiple Output Fifth Generation Millimeter Wave Device-to-Device User Equipment Base Station Internet of Things Dynamic Channel Allocation Line-of-Sight Non Line-of-Sight Inter Symbol Interference Medium Access Control Heterogeneous Network Vehicle-to-Vehicle Machine-to-Machine Quality of Service Long Term Evolution Channel State Information Resource Block Signal to Interference Noise Ratio Additive White Gaussian Noise Single User Water-filling Non-linear Programming Mixed Integer Non-linear Programing xii

13 List of Notations P L freespace R T X RX λ P T X P RX G T X G RX P L R η N N o N c,u N s B n e p c, n p d, n N n γ c γc th γ d γd th h ab K L P n q J M Free Space Path Loss Distance between the transmitter and receiver Wavelength Total transmit power Total receive power Transmitting antenna gain Receiving antenna gain Path Loss Data Rate Spectral Efficiency Total RB at the BS RB dedicated for Overlay mode RB available for cellular and underlay D2D mode RB already allocated to users Bandwidth Bandwidth Efficiency of a RB nϵn Cellular user transmit power using a RB nϵn D2D user transmit power using a RB nϵn Thermal noise SINR of cellular user SINR threshold of cellular user SINR of D2D user SINR threshold of D2D user Channel gain between the two links a and b Cellular users in a cell D2D users in a cell Maximum transmit power of a D2D user using RB nϵn probability Number of D2D connection requests Maximum number of active users per a resource block xiii

14

15 Chapter 1 Introduction 1.1 Introduction and Motivation The recent innovations and technological developments in the field of communication focus on serving the ever growing demand for bandwidth. Along with the advancement in bandwidth intensive applications, the number of devices per unit area is also increasing drastically. The current fourth generation (4G) cellular systems using the technologies like Orthogonal Frequency Division Multiplexing (OFDM), Multiple Input Multiple Output (MIMO), massive small cell deployment, Heterogeneous Network (Het Net) and relays are able to improve the spectral efficiency. But these technologies would not be able to serve the increasing demand for higher bandwidth in future [1]. Hence, researchers are seeking new revolutionary paradigms in cellular communications. Therefore, the fifth generation (5G) cellular technology would be developed to overcome the spectrum shortage and serve more number of users, beyond 4G [2]. The 5G technology would exploit Millimeter Wave (mmwave) spectrum for communication, where the spectrum is unparalleled compared to the cellular systems operating in microwave frequencies [3]. Device-to-Device (D2D) communication is a direct communication between two mobile users in proximity within a cellular network without traversing the base station, and is a disruptive technology direction for 5G [4,5]. D2D communication can give the advantage of high data rate, increased spectral efficiency and also improves throughput and delay [6]. It can also offload the base stations while achieving a better performance and avoid congestion [7]. In addition to the above mentioned advantages, it coexists with traditional cellular communication. The 5G cellular technologies are developed to overcome the spectrum shortage by exploring the mmwave spectrum [8]. Due to high frequency, short distance attenuation properties and atmospheric absorption, mmwave communication is a short range communication [3]. Outdoor propagation provides rich multi-path at and above 28 GHz frequency, exploiting which the received signal power can be improved [9]. Directional beamforming and smart antennas improve the propagation with high quality links [5]. Therefore, the integration of D2D technology with mmwave communication will gain the advantages of both the technologies. 1

16 1.2 Next Generation Wireless Technologies The next generation (5G) technologies need to be a paradigm shift which include very high carrier frequency with massive bandwidth, high density of base stations and devices, and very large numbers of antennas [10]. The traffic demand is growing exponentially from day to day. Most of the wireless traffic demand is dominated by intensive data applications like video multimedia [3]. This leads to the expectation of Giga bits per second (Gbps) data rates and low latency [11]. Moreover, the emerging technology of Internet of Things (IoT) requires more number of connected devices per unit area. The following are the goals and requirements that are expected to reach in 5G cellular technologies: 1. High system capacity: The system capacity is expected to increase by 1000x capacity/km² than the existing 4G technologies [8]. 2. High data rate: The data rate achieved is expected to increase by x with and without mobility [3]. 3. Massive device connectivity: The number of devices connected to internet is expected to increase by 100x times than the presently connected devices in 4G [12]. 4. Energy saving and cost reduction: The 5G technologies try to achieve energy efficiency systems at low cost [13, 14]. 5. Reduced latency: The expected latency is <1ms in 5G technologies [5]. This thesis aims at achieving the goals of massive device connectivity with high rate in 5G cellular systems. The detailed discussion of emerging technologies for next generation is in [5]. Inter-cell interference in cellular networks is a well-known challenge from beginning of the mobile radio networks. The inter-cell interference coordination techniques include frequency reuse and Dynamic Channel Allocation (DCA). They play a vital role in improving the spectrum efficiency. The techniques of frequency reuse are very sophisticated. Depending on the traffic demand, channels allocated to each cell is varied in DCA [15]. In OFDM based cellular systems, the channel information and interference signals can be measured easily whose knowledge is essential to improve spectrum efficiency [16]. In [16], it is explained that in OFDM systems, DCA can improve the spectral efficiency to a great extent. The next generation cellular systems would incorporate small cell (Micro, Pico and Femto) base stations for extensive frequency reuse and spectrum utility [17]. Heterogeneous networks are proposed as one among the technologies that will enable integration of micro, pico and femto cells with the macro cells [18]. With high frequency reuse in small cells, the available spectrum for communication is efficiently utilized [19]. 2

17 1.2.1 Millimeter Wave Technology The desire for higher data rates with lower delays and constant connectivity on wireless devices needs to be fulfilled by 5G cellular technologies. The communication at mmwave frequencies is a recent game-changing technology in wireless communication systems. At these frequencies, the electromagnetic spectrum is unparalleled compared to the present cellular spectrum which is operating below 10 GHz [3]. The unlicensed band at 60 GHz offers 10x more than the conventional ISM band. The unlicensed 60 GHz spectrum is available throughout the world [3]. The mmwave signals have their range of wavelengths from 10 mm to 1 mm. Consequently, the electromagnetic spectrum corresponds to the radio band frequency of GHz [8]. The spectrum at 28 GHz, 38 GHz and GHz is promising for in next-generation cellular micro- and pico-cellular wireless networks [3] because of their propagation characteristics. The spectrum at 28 GHz is slightly lower than the mmwave frequency range and hence has lower path loss [3]. The E band mmwave frequencies are 28 GHz, 38 GHz and 73 GHz. World s cell phones are presently operating in less than 3 GHz spectrum. The spectrum for mmwave is illustrated in Figure 1.1 [5]. The available spectrum at these frequencies can be 200 times greater than the current cellular allocations [9], and provides more resources which can be shared among multiple users. In millimeter wave free-space propagation, the signal power attenuates proportional to the square of the range. This is because of the spherical spreading of the propagating radio waves. The line-of-sight (LOS) propagation occurs if there are no blockages for the signal in its path from transmitter to the reference receiver. Otherwise, in case of blockage of signal in its path it is called non-line of sight (NLOS) propagation. The LOS path loss between two isotropic antennas is [8]: ( P L freespace = 20 log 10 4π R ) T X RX db (1.1) λ where, P L freespace is the free space path loss, R T X RX is the distance between the transmitter and receiver and λ is the wavelength. The above equation illustrates that the free space path loss increases with frequency and range. Also, the equation shows that the LOS path loss increases with increase in range or frequency and the path loss can be quite high for short distances. Therefore, it can be inferred that mmwave spectrum is best suitable for short distance communication links. This also enables high level of frequency reuse. Another way to express path loss is using Friis Law which accounts for all the factors for theoretical calculation [9]. The path loss of mmwave propagation using Friss Equation [8] is as follows: P RX = P T X G RX G T X λ 2 (4πR T X RX ) 2 L (1.2) 3

18 Figure 1.1: Millimeter wave spectrum [5] where, P T X is the total transmit power, P RX is the total integrated receive power over all angular directions, G T X and G RX are transmitting and receiving antenna gains respectively and L is the system loss factor ( 1). The channel model used in this thesis considers Friis Law theoretical calculation for path loss [3,8,9,20]. In addition to the main source of transmission loss, i.e. free-space loss, mmwave has other loss factors in the transmitting medium. The absorption loss factors are atmospheric gases attenuation due to oxygen and water vapor absorption, human shadowing and scattering effects due to reflections [20]. These losses due to water and oxygen are higher at certain frequencies as they coincide with mechanical resonant frequencies of the gas molecules [8]. This effect of mmwave communication is compounded by other unfavorable qualities like decreased signal penetration through obstacles, high antenna gain requirement for directional communication and substantial ISI due to many reflective paths [3]. In an environment with dense users and obstacles, line of sight (LOS) may not be practical and the received signal is characterized by signal copies of different delays and angular separation [21]. Therefore, in such a scenario, the received signal experiences a path loss which contains line of sight (LOS) and non line of sight (NLOS) components corresponding to their respective log-normal shadow fading [21]. The path loss is estimated by the following formula [3, 9, 20]: P L(d)[dB] = α + β10 log 10 (d) + ζ where d is the distance in meters, α and β correspond to the floating intercept and slope and ζ is the log normal random variable zero mean and standard deviation, σ in decibels to model the shadow fading [3]. The path loss values for both LOS and NLOS considered for simulation in this work are referred from [3, 9] which are suitable for use in 3GPP standards. The (α, β) models for 28 GHz frequency with reference to 1 m free space distance model (according to 3GPP standards) for varying distances is discussed in [3]. 4

19 The mmwave channel analyzed with the above equation, has some free-space propagation characteristics which are similar to the conventional microwave frequency channel and also differs from it making the analysis of mmwave channel more challenging. The properties of mmwave that are similar to microwave frequencies are distance-dependent path loss and possibility of non-light-of-sight communication. The properties of mmwave that are different from microwave frequencies are sensitivity to blockage and high power consumption of Analog-to- Digital Converter (ADC) and Digital-to-Analog Converter (DAC) circuitry. Microwave propagation is characterized by Rayleigh fading. Rayleigh fading is based on the assumption of a large number of scatters in the channel. After the application of the central limit theorem it results in a Gaussian model, leading to the Rayleigh distribution of the channel response envelope for the zero-mean channel. A zero mean approximation applies when there is no line of sight path between transmitter and receiver. When there is a predominant line-of-sight between receiver and transmitter Rayleigh fading no longer holds because the mean value of (at least) one component is non-zero due to a strong wave, in addition to the Rayleigh fading. The channel is described as Rician with the channel response envelop distributed according to Rice distribution. Hence, Rician fading is considered in mmwave propagation. The shift from long range communication to close range communication is beneficial as it allows aggressive frequency reuse without interference in simultaneously operating networks. In-spite of indoor propagation, mmwave communication in outdoor urban environments at and above 28 GHz frequency provides rich multi-path which can be exploited in non-line of sight (NLOS) propagation to improve the received signal power [3]. The scattering effects in mmwave frequencies cause the weak signals to become an important source of diversity and NLOS paths are weaker. In order to have high quality links, directional beamforming is adopted at both the base station and user equipment which improves the propagation [22]. Hybrid beamforming and precoding techniques are used while limiting the hardware [23]. The architecture of mmwave cellular network in 5G would be a heterogeneous network [18] and different than microwave systems. Aggressive spatial reuse is possible if there exist directional beamforming links between base station (BS) and the hand-set [24]. This also reduces the outof-cell interference. The mmwave cellular systems can be integrated with microwave systems and they can make use of the microwave systems. The control information can be sent on microwave frequencies and data is sent on millimeter wave frequencies whenever possible. The authors in [3] describe a handover model where communication is supported at both microwave and mmwave carrier frequencies simultaneously. They convey that a Medium Access Control (MAC) protocol can support the transfer from mmwave link to microwave link and vice versa. The spectrum at 28 GHz is seeking more attention because of its better propagation characteristics than the other mmwave frequencies. Recently, the analysis of channel model at mmwave frequencies is characterized by conducting practical experiments. The experiments at 28 GHz and 73 GHz frequencies are conducted in New York City [9,20] and at 38 GHz are con- 5

20 ducted at Austin, which are two major cities of USA [20]. The authors in [20] also discuss the wireless evolutions and requirements till the present day and technological aspects beyond 4G along with the current 2G, 3G, 4G and LTE-A bandwidth and spectrum allocations. They also provide detailed experimental results for 28 GHz mmwave propagation in urban areas and its propagation characteristics. In [9], the propagation at 28 GHz frequency in outdoor scenario is analyzed with the aid of practical experimental results in New York city. They also discuss the aspects of LOS and NLOS propagation of mmwave due to atmospheric absorption and signal fading due to obstacles. The results derived in [9] are used for the channel model in this thesis. Rician fading is used in analyzing the mmwave propagation and not Rayleigh fading. Rician fading is used in the mmwave channel model at 28 GHz frequency band [25]. In [9], the models based on experimental data reveal that the signals at 28 GHz and 73 GHz can be detected at least 100 m to 200 m from the potential cell sites, even in the absence of LOS propagation. The signals at many locations arrived with multiple path clusters due to building reflections to support spatial multiplexing and diversity [9]. The cellular capacity evaluations based on these models in [9], predict an order of magnitude increase in capacity than the current 4G systems. 1.3 D2D Communication D2D communication is a direct communication between two mobile users in proximity within a cellular network without traversing the base station. In 4G networks, D2D communication is admitted to be a feasible solution to overcome the spectrum scarcity [6]. The 5G cellular systems employing D2D communication can support the huge demand for bandwidth and improve the spectrum efficiency to a great extent. In [4, 24], D2D communication is discussed as a disruptive technology direction for 5G. D2D communication is currently specified by 3GPP Rel-12 [26]. The recent trends in D2D communication have escalated the importance of proximity based services for next generation cellular systems. In proximity based services, devices detect their proximity and trigger the services with local exchange of information. In case of infrastructure failure, the devices can have local connectivity for public safety [27]. Also, smart communication between vehicles is possible which is called vehicle-to-vehicle (V2V) communication [28]. Since, it coexists with the cellular spectrum, it interferes with the licensed band. Hence, good interference management techniques need to be adopted. The device design is to be taken care of in case, if dedicated resources are used for communication. Security and mobility management are major challenges in proximity based services [29]. It can be said that the diverse cellular networks allow user devices to directly communicate with each other and are controlled by the base station in D2D communication. Since, the devices in a D2D link are closely located to each other, the communication allows for high data rate at low latency and also low energy consumption. By using an efficient method to reduce the transmit power of the devices, the interference can be managed well such that 6

21 Figure 1.2: Illustration of benefits and use cases of D2D communication [26] the reuse of transmission resources is possible within the same cell [30]. However, the exact amount of gain and benefits because of direct link connectivity need to be quantified. In D2D communication, the problems of resource allocation, power allocation and interference management are more challenging than in conventional network infrastructure because of the dynamic nature of wireless links. The research area which is receiving increasing attention is to find mechanisms for incorporating D2D technology into the existing cellular networks. Another interesting area is the design of application scenarios like the direct communication between vehicles. D2D communication techniques can be used in cellular offloading, relaying, Machine-to-Machine(M2M) communication, content distribution and gaming applications [6]. Figure 1.2 [26] shows the use cases of D2D communication and some potential benefits. D2D is similar to Mobile Ad-hoc Networks (MANETS) and cognitive radio technology from architectural perspective. M2M communication is basically the data communication between machines which is similar to D2D communication. D2D communication is controlled by central entity and autonomous when cellular infrastructure is unavailable. But the following are the key differences between the technologies [6, 31]: One of the key difference among the three technologies is the involvement of the cellular network in the control plane. The base station is involved in managing the communication in D2D which resolves challenges of cognitive radio and MANETS such as collision avoidance, synchronization and white space detection. Mainly, D2D communication is a single hop communication. Hence, it does not have the problem of multi-hop routing as in MANETS. M2M communication does not need human interaction whereas D2D communication necessarily requires human interaction. 7

22 M2M communication does not have any constraint on the distance between the nodes. In case of D2D communication, the communication range is specified. M2M communication is technology independent and application oriented while D2D communication is proximity based service and is technology dependent. In brief, D2D gains the advantages of high gain, low attenuation, low transmit power and good spectral efficiency. D2D communication technology has new challenges of device design, infrastructure management, interference management, security and mobility management. Basically, M2M communication is a use case of D2D communication. The massive connectivity between machines requires techniques to coordinate access and allocate resources. Other than adapting the traditional communication techniques, an efficient method will be a direct communication between the devices. This can help in avoiding congestion and cell overload. In [31], a novel aggregation technique is proposed exploring D2D connectivity for users in machine-type devices. In M2M communications, millions of devices communicate with each other without human intervention and is a key enabler for Internet of Things (IoT). The Quality of service (QoS) can be considerably improved by employing D2D communication techniques in IoT. A detailed survey on the usefulness of D2D technology in IoT is presented in [32] Comparison between Traditional Communication and D2D Communication In traditional communication techniques, all the communication traverses through the base station even if the devices are in proximity. This suits the conventional low data rate communication while in D2D communication, since the devices are in proximity, high data rates can be achieved with low latency [6]. Traditional communication needs uplink and downlink resources to communicate whereas, D2D communication needs less number of resources.i.e., only one resource is required to establish a link between the users [30]. D2D technology can also provide public safety by providing local connectivity among devices incase of infrastructure failure [26]. D2D can achieve higher throughput and can highly increase the spectral efficiency and energy efficiency. This is because, the devices communicating are in proximity and hence, the range is less resulting in lower path loss and better received signal strength compared to traditional communication. Efficient methods need to be developed in allocating resources and decreasing computation overhead in D2D communication. Also, the device design needs to be improved in case dedicated resources are used [6]. Traditional communication can be more advantageous when the number of devices for connectivity are less and if the devices are not in proximity Taxonomy D2D communication is broadly classified into two types based on the spectrum resources used for its operation. D2D communication can operate in the cellular spectrum, called the 8

23 Figure 1.3: Classification of D2D communication inband or can use unlicensed spectrum, called the outband [6]. The interference in unlicensed band is higher compared to that in the licensed band. Hence, most of the research is focused on inband D2D communication because of the uncontrollable interference in unlicensed band. The taxonomy of D2D communication is illustrated in Figure 1.3. The illustration of how the spectrum resources are shared in different types of D2D communication is illustrated with a schematic representation in Figure 1.4 [6] Inband D2D communication Inband D2D communication is further divided into underlay mode and overlay mode of operation based on how the spectrum resources are shared for D2D communication. In underlay mode, both the cellular user and D2D user use the same resources maintaining the interference level as low as possible. The spectrum efficiency is increased to a great extent with underlay mode [33]. The overlay mode D2D communication uses dedicated cellular resources for operation. This implies that there exists no interference between cellular and D2D user. But since the precious resources are dedicated for D2D operation, in case of absence of users in proximity, these resources will be wasted. The main challenge in inband D2D is the interference between D2D users and cellular communications. To mitigate the interference, high complexity resource allocation methods are introduced, which increase the computational overhead of the BS or D2D users. Underlay D2D Communication Underlay D2D achieves better spectral efficiency, power efficiency, QoS, fairness, reliability and cellular coverage [6]. Existing research work focuses on the importance of inband underlay D2D communication in increasing spectrum efficiency and methods for resource allocation [33, 9

24 Figure 1.4: Schematic representation of inband overlay, inband underlay, and outband D2D communication [6] 34]. Underlay mode is shown to have the advantage of spectral efficiency and better QoS with efficient interference management in [35]. The uplink performance metrics for inband underlay D2D are discussed in [36] which emphasizes on the effect of interference from adjacent D2D user. In [37], the authors use a network science approach for D2D communication for energy efficiency (30% improvement) and delay (15% improvement). In [38], a joint spectrum and power allocation framework is proposed based on pricing with QoS guarantee. The interference between cellular users and D2D users is controlled by the base station by setting a price for each D2D channel used. In order to achieve this, a game-theoretic approach is used where the D2D pairs compete for the spectrum until a Nash equilibrium is achieved. The system performance and the speed of convergence of the proposed algorithms are shown in simulation results of [38]. In [39], a fair resource allocation problem for D2D communications in OFDMAbased wireless cellular networks is discussed. They propose waveforms that can be used for D2D communication which can improve delay and achieve maximum rate. Overlay D2D Communication In overlay mode, the absence of D2D users makes the spectrum underutilized but simplifies the resource allocation as the cellular user interference does not exist. However, overlay mode can achieve better throughput performance [40]. In [41], the work analyses overlay D2D coexisting with OFDM network. They show that the interference in the network due to both frequency and time misalignment. In [42], a scheme is proposed to mitigate interference between the D2D users in overlay mode reusing the resources. Another interesting area in D2D communication 10

25 is mode selection between cellular mode and D2D mode. Mode selection is discussed in detail in [43]. The authors in [44], discuss the mobility impact on mode selection using an analytical approach Outband D2D communication In outband D2D communication, the D2D links exploit unlicensed spectrum. The interference between cellular and D2D users is absent in outband. The outband D2D communication is further divided into controlled and autonomous mode of operation. Using the unlicensed spectrum would require an extra interface and also, usually adopts other technologies like WiFi Direct [45] or bluetooth [46]. In [47, 48], the work suggests control of interference to cellular network i.e., controlled outband D2D communication. In contrast to this the cellular communications can be controlled and D2D communication can be left to users. This is called autonomous and is discussed in [49]. D2D and cellular users. Outband D2D communication may suffer from the uncontrolled nature of the unlicensed spectrum. It should be noted that only the devices which have two wireless interfaces (e.g., WiFi and LTE) can use outband D2D. Therefore, the users can have D2D communication and cellular communication simultaneously Integration of D2D Communication and mmwave Technology The next generation systems employing mmwave technology (short range communication) integrated with D2D (devices in proximity) communication would gain the advantage of high bandwidth and spectrum efficiency. Also, mmwave is a short range communication and D2D communication is between the devices in proximity boosting the advantages of their combination. D2D communication technology offloads the BS, achieving better system performance, avoiding congestion, and coexists with traditional cellular communication [4, 7]. The spectrum currently available for cellular communication is already congested with traffic. Therefore, the 5G technology exploits mmwave spectrum for communication [3]. In [24], authors describe about the advantages of integrating mmwave technology with D2D communication for 5G networks. The work in [50] uses stochastic geometry to analyze the performance of mmwave networks with a finite number of interferers in a finite network region when the devices communicating are indoor. The path loss in D2D communication using mmwave propagation in urban environment is discussed in [51]. 1.4 Thesis Contributions As mentioned in the previous section, some of the the 5G goals can be met by D2D technology. This work tries to reach the goals of high data rate and massive device connectivity. In this work, inband D2D communication is considered because of good interference control over the cellular spectrum and a selection between underlay and overlay mode is done to 11

26 maximize the QoS and spectrum utility. There exist many heuristic and greedy algorithms in literature for underlay D2D but the work in mmwave spectrum band is relatively less in an outdoor scenario. Also, the number of resource blocks available for allocation in mmwave bands is more than that in 4G (LTE-A) systems. According to the conveyed literature, there are no prior works integrating underlay and overlay modes, particularly using mmwave propagation. One of the contributions of this work is to minimize spectrum wastage in overlay mode for which the resources allocated to overlay mode are rescheduled based on the call traffic density. A prediction based model is used by collecting the historical call traffic data. Next, a major challenge is to mitigate interference which is addressed using efficient resource allocation methods. The resource allocation problem is formulated to maximize QoS, addressing power control and interference management. To overcome the problem of increased computation overhead and scheduling time at the BS, a single algorithm is proposed for mode selection, resource allocation and power control with avoiding interference. In summary, the addressed problems are as follows: Dynamic mode selection, spectrum management, power control and interference mitigation are jointly addressed to improve QoS. Efficient scheme for resource management is proposed in the following two aspects for underlay mode D2D communication. 1. Resource block sorting can improve the performance in case of availability of instantaneous CSI. 2. Fair resource block allocation is used to avoid congestion over the resource block, particularly using above method (in 1). Achieving better system performance (maximizing throughput) using millimeter wave channel model. Improving spectrum utility and decreasing underutilization, which is the main disadvantage of overlay mode D2D communication. Emphasis on the advantages of overlay mode and selectively switching to overlay mode. Single resource allocation algorithm which serves for both the modes (underlay and overlay). 1.5 Thesis Organization The rest of the thesis is organized as follows. Chapter 2 describes D2D communication in underlay mode using the mmwave technology. The work is subdivided as follows: section 2.1 describes the system model with multiple D2D connections using mmwave channel model 12

27 for signal propagation. The usefulness of mmwave propagation in D2D communication is discussed. Section 2.2 describes the problem formulation and section 2.3 discusses the algorithm to solve the formulated problem. The simulation results are presented in section 2.4 and a brief summary of the chapter is given in section 2.5. The next chapter describes the improvement of underlay D2D communication with power control and fair resource allocation with the following sections. Section 3.1 describes the related background work for vivid understanding. The system model for network controlled D2D communication is presented in section 3.2. The problem formulation and proposed suboptimal algorithm are proposed in section 3.3 followed by the simulation results in section 3.4 and summary in section 3.5. In chapter 4, the inband D2D communication is discussed with the following sections. In section 4.1, background related to inband (both underlay and overlay) is presented. Section 4.2 describes the system model and mode selection. In section 4.3, the problem of assigning dedicated resources to overlay mode is described and the proposed mechanism and simulation results are also presented. In section 4.4, the second problem is formulated for joint power allocation, mode selection and resource allocation and a heuristic is proposed to solve the problem. The performance of the proposed algorithm is evaluated with simulation in section 4.6. Thesis conclusion is presented in chapter 5 with a few future directions for research. 13

28 Chapter 2 D2D Communication as an Underlay to 5G Cellular Systems As already discussed in the previous chapter, D2D communication is classified into underlay mode and overlay mode. In this chapter, underlay D2D communication is discussed with emphasis on its integration with mmwave technology. The problems of resource allocation and interference avoidance aiming for better spectral efficiency are addressed. 2.1 System Model A 5G cellular network incorporating D2D communication in a single cell environment is considered in this work. The BS, at the center ensures the entire cell coverage and can serve N number of resource blocks to K number of cellular users and L number of D2D users. Consider a scenario where one resource block is shared by more than one D2D user in underlay mode. In such a case, where the radio resources are shared, to maintain the performance, interference to the cellular network as well as to the other D2D connections must be maintained below a threshold level. With the increase in the distance between D2D pair, the transmission power for D2D also increases causing more interference to the network [52]. The system model for multiple D2D pairs who share the same radio resources with cellular users is shown in Figure 2.1. The scenario with two adjacent cells, Cell-A and Cell-B is considered. The resource allocation for users in Cell-A is addressed in this chapter. Cell-B is used to illustrate the scenarios and hence is colored differently than Cell-A. Also, the users in Cell-B are given a subscript b. The user D k experiences interference from D2D users D 2 and D 3 who are sharing the same resources of a cellular user U k. These interference levels must be maintained below a threshold value. It also experiences interference from U b2 and D b4 from the adjacent cell, Cell-B, which is called inter-cell interference (ICI). Consider a scenario in Cell-B, where the line of sight propagation encounters an obstacle in its path. The mmwave signal will experience a high path loss if the BS has to coordinate the entire communication. In such a situation, D2D communication can give considerable improvement to the system performance since the BS only needs to send a control signal and the communication takes places only between the devices without traversing the base station. This is illustrated in Figure

29 Figure 2.1: System model for multiple underlay D2D communications in a cell illustrating interference between D k,u k, D 3, U b2 and D b4 The interference is not only because of the transmit power but is also caused by the spatial separation between two users (cellular or D2D) reusing the same resource block. More than one D2D pair reusing the same resource block in this work so, the maximum allowable distance between D2D devices is considered as 20 m [52]. If the device separation distance exceeds this range, the communication is handed over to the BS. It is assumed that the cellular and D2D connections mentioned are in the same cell. A single BS is coordinating the entire communications in a cell,.i.e., both cellular and D2D communications. The BS and the D2D users are assumed to have the knowledge of the interference threshold and of instantaneous channel state information (CSI). This assumption is necessary to control the D2D communication by the BS within a short scheduling time. In LTE system, the instantaneous CSI can be obtained by using reference signals. The same method can be followed for 5G cellular systems. The D2D pairs reuse the resource block (RB) of a single cellular user as long as the CSI is favorable Channel Model The channel model for mmwave propagation used for communication between a D2D pair is discussed in section of Chapter 1. The licensed spectrum at 28 GHz is considered for 15

30 outdoor propagation conditions. The path loss values considered for simulation in Table 2.1 are taken from [9]. Multipath fading in mmwave communication is more likely to be Rician channel rather than a Rayleigh channel. 2.2 Problem Description The total set of resource blocks available at the base station is N = {1, 2,..., n} and in uplink mode serves a set of K = {1, 2,..., k} cellular users. Each user is specifically given a resource block denoted by r bn where, n varies for different resource blocks. These cellular users share the same radio resources with a set of L = {1, 2,..., l} D2D users such that K N and also L N such that K L i.e., the number of D2D users reusing the resources exceed the cellular users in the cell. For the efficient usage of spectral resources, D2D pairs reuse the RB of a cellular user when the interference level is below the threshold requirement of signal to interference noise ratio (SINR). The SINR of cellular user denoted by γ c is as follows: γ c = p c h b,c L d=1 [x d,cp d h d,c ] + c [y c p c h b,c ] + N n γ th c (2.1) where, c = 1, 2,..., K. and p c is the cellular transmit power, p d is the device transmit power. h b,c, h c,d corresponds to the channel gain between the BS to cellular user link and channel gains between cellular and D2D links. N n corresponds to the Additive White Gaussian Noise (AWGN) in the channel. x c,d is a binary variable which is set to 1 in case the D2D user is sharing the same RB of CU and y c is set to 1 in case the same RB is shared by user in the next cell. The interference is the sum of inter-cell interference and within a cell. The term c [y c p c h dc ] corresponds to interference from the adjacent cell using the same RB,and is further denoted as I ICI. The value of γ c must be maintained greater than a threshold γc th. Similarly, the SINR of D2D must be maintained above a threshold, γd th which is expressed as follows: γ d = where, d = 1, 2,..., L and x c,d p d h d,d K c=1 [x c,dp c h c,d ] + I ICI + d [x c,d p d h d,d ] + N n γ th d (2.2) is a binary variable which is set to 1 if another D2D pair, d is allocated the same RB. In the absence of more than one D2D links, the term, d [x cd P d H dd ] will be zero and the resulting SINR for D2D can be denoted as γ d. Let a new user equipment, u is trying to use the same resource block (either on D2D mode or on cellular mode), the interference experienced by u is the because of both γ c and γ d. γ u = (u c )p c h b,c L d=1 [x c,dp d h c,d ] + (1 u c )p d h d,d c [y c p c h b,c ] + N + K n c=1 [x c,dp c h c,d ] + I ICI + d [x c,d p d h d,d ] + N n(2.3) If the user, u is assigned a cellular mode then, u c is set to 1. Otherwise, if user, u is assigned D2D mode then, the value of u c is set to zero. 16