Online Distributed User Association for Heterogeneous Radio Access Network

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.

Network Offloading schemes play a vital role when there is a massive growth in the capacity of Next Generation Networks. The aggregation of LTE (Long Term Evolution) and WLAN (Wireless Local Area Network) is meant to provide service with seamless connectivity for the User Equipment (UE). There are two major issues that have been identified in existing RSSI (Received Signal Strength Indicator) based offloading scheme such as: i) it fails to provide better performance ii) it requires frequent reconnection for establishing dual connectivity. UE (User Equipment) based offloading approach requires a lot of signaling between UE and Radio access network and thus lacks in resource utilization and energy efficiency. Network based offloading approach needs a network specific entity. In the proposed LWA-SA (LTE WLAN Aggregation-SDN Assisted) which is an SDN (Software Defined Networking) based offloading scheme. In this, a controller keeps track of ongoing sessions after offloading. Here, an algorithm is used based on Access Network Discovery and Selection Function (ANDSF) offloading scheme for the purpose of selecting an efficient Wi-Fi access point which increases the throughput and reduces the delay and also provides seamless connectivity to the UE.

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.

Mobile Networks today comprise of multiple Radio Access Technologies (RATs), e.g., 4G Long Term Evolution (LTE), Wireless Local Area Network (WLAN), and the upcoming 5G-New Radio (5G-NR). The access networks of these RATs are controlled by RAT-specific entities, e.g., the resource management function located inside an individual LTE eNB is used for the eNB control, or access controllers are used for controlling WLAN access points. Even in the 3rd Generation Partnership Project’s (3GPP) 5G architecture, which has a common Core supporting multiple RATs, radio access related decisions are taken independently within individual RATs. Due to the fragmented nature of control-plane in multi-RAT Radio Access Network (RAN), a unified global view of network resources is unavailable, hindering optimized allocation of resources. It also brings complexity to the features involving multiple RATs, e.g., dual connectivity. To address these issues, we introduced an SDN-based Multi-RAT RAN architecture (SMRAN) in our earlier work [1], where the RAN control-plane is segregated from the data-plane. As part of the SMRAN architecture, we defined a logically centralized multi-RAT RAN Controller and individual RAT- specific data-plane functions. In the current work, we define a protocol, called Open5G, to be used for control and management of the SMRAN data-plane. Open5G is based on OpenFlow (OF) and OF-Config, which are commonly used protocols in the SDN-based wired networks and data centers. With the Open5G protocol, the multi-RAT RAN can be controlled by an open interface, bringing flexibility and simplicity in network interactions.

As we are leaving in 5G era which promises us to give high throughput rate, better efficiency rate, and high bandwidth etc as its feature make headlines to give advanced and enhanced services in various sector whether it could be IOT, infrastructure, agriculture, and health care [1]. Giving well-grounded communication technology possesses a fundamental challenge for 5G system in both Core network and Radio Access Network (RAN) levels [2]. To get a better credibility at RAN level, base station (EnodeB or gNodeB in 4G and 5G respectively) should allocate proper amount of resource as per UE and select appropriate Modulation and scheme (MCS) to give better user experience. The amount of Physical Resource Blocks is directly proportional to channel condition at the User Equipment (UE) end [5]. The Base Station would generally know the real time channel strength of each UE, which then later provides accordingly resource to the UE, as UE would be sending periodically CQI to Base station. However, the periodic transmission of CQI would lead to signaling overhead which hampers the performance of RAN. Henceforth its foremost thing to average it or to optimize the CQI value to give a better user experience. Therefore, will be exploring four such machine learning algorithms (ANN, reinforcement learning, KNN and SVM) to optimize the CQI and would be analyzing which Algorithm will give better performance. Key Words: CQI, Machine Algorithm, RAN, Offloading, Handover, Base Station

현재 사용되고 있는 대표적인 무선 네트워크 접속 기술들로는 높은 이동성을 지원하는 휴대 전화망인 WWAN(Wireless Wide Area Networks), 높은 대역폭을 지원하는 WLAN(Wireless Local Area Networks), 그리고 방송 및 데이터를 수신할 수 있는 WDMB(Wireless Digital Multimedia Broadcasting) 등을 들 수 있다. 그러나 각각의 기술들은 각각 이동성 및 데이터 전송률, 그리고 데이터의 방향성 등의 한계를 내포하고 있다. 이러한 제약점을 극복하기 위해, 서로 다른 접속 기술을 상황에 따라 전환하여, 현재 서비스 받고 있는 데이터 접속을 끊김없이 연결해 주어야하는 수직적 핸드오프(Vertical Handoff) 기법에 대한 연구가 활발히 진행 중이다. 본 논문에서는 WWAN 인터페이스를 기반으로, 단말에 장착되어 있는 다른 인터페이스들(WLAN과 WDMB)에 대한 에너지 소모를 최소화하여 전체 시스템의 생명시간(Life time)을 최대화하는 인터페이스 선택 알고리즘과 망구조를 제안한다. 또한 다양한 서비스에 대한 트래픽을 분석하여 망단에 존재하는 사용자 버퍼를 관리하고 이를 수직적 핸드오프의 기준으로 활용하여 기존 방식들에 비교하여 전체적 에너지 소모가 기존 기법 대비 각각 <TEX>$75\%$</TEX>(WDMB 우선), <TEX>$34\%$</TEX>(WLAN 우선) 절감됨을 보인다. There are a few representative wireless network access technologies used widely. WWAN is celluar based telecommunication networks supporting high mobility, WLAN ensures high data rate within hotspot coverage, and WDMB support both data and broadcasting services correspondingly. However, these technologies include some limitations especially on the mobility, data rate, transmission direction, and so on. In order to overvome these limitations, there are various studies have been proposed in terms of 'Vortical Handoff' that offers seamless connectivity by switching active connection to the appropriate interface which installed in the mobile devices. In this paper, we propose the interface selection algorithm and network architecture to maximize the life time of entire system by minimizing the unnecessary energy consumption of another interfaces such as WLAN, WDMB that are taken in the user equipment. In addition, by using the results of analyzing multiple types of traffic and managing user buffer as a metric for vertical handoff, we show that the energy efficiency of our scheme is <TEX>$75\%$</TEX> and <TEX>$34\%$</TEX> than typical WLAN for WDMB and WLAN preferred schemes, correspondingly.

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.

5G-Flow: A unified Multi-RAT RAN architecture for beyond 5G networks

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.

Conventional planning and optimization of cellular mobile networks for supporting the peak-time user demand leads to substantial wastage of electrical energy. Infrastructure sharing among geographically collocated networks is considered promising for energy efficient operation of future cellular systems. Therefore, this paper proposes a generalized energy-efficient cooperation framework for sharing BSs between two cellular radio-access networks (RANs) serving the same geographical area. Previous works have the constraint of cooperation only among the collocated BSs belonging to different RANs, while the proposed framework is free from such limitation. To the best of our knowledge, this paper is the first for developing cooperation mechanisms among the non-collated BSs. Independent Poisson point process is used for modeling the near realistic random locations of both BSs and user equipment (UEs). Under the proposed framework, BSs belonging to different RANs dynamically share each others traffic and thus allow some BSs to switch into low power sleep mode for saving energy. During this BS switching through traffic-sharing, connection continuity (no drop of the existing calls) is maintained throughout the network. A generalized optimization problem for maximizing energy savings is formulated. Due to the high complexity of the optimization problem, heuristically guided algorithms differing in BS selection and UE association policies are proposed. More specifically, two different BSs selection schemes and three separate UE association policies are integrated in the algorithms. Performance of the proposed inter-RAN cooperation framework is evaluated using extensive simulations demonstrating a substantial energy savings and gain in energy efficiency. Impact of different network parameters, such as BS selection and UE association policies, BS and UE densities, BS power profile and SINR requirements for connection continuity on the system performance is thoroughly investigated and analyzed.

To establish the best connection possible, different radio access technologies are combined to form a heterogeneous wireless network (HetNets). The HetNets consists of macro cells and small cells in the Long Term Evolution-Advanced (LTE-A) network. However, the fast pace of development of LTE-A technology has been very challenging due to the increase in the number of user equipment (UE). Managing the selection of the target cell and migration of active communication sessions of the UE between different base station (BS) points is vital for seamless mobility. To address this issue, a multi-criteria eNodeB pre-selection parameter is introduced to pre-select the most suitable cell for handover. The proposed approach aims to enable UE to autonomously assess a list of potential eNodeB located in their direction of movement and choose the most suitable candidate network. A framework for eNodeB selection is developed that considers the distance between the candidate network and the vehicle's trajectory, as well as the mobility information of the vehicle. The important parameters which are the proximity index and distance factor are chosen to identify the best candidate eNodeB. Moreover, we investigate an efficient scheme for the handover trigger to get an optimum distance for handover initiation using the particle swarm optimization (PSO) technique. The results show that to reduce unsuccessful handover, the proposed parameters are reliable for eNodeB selection to self-select the network and improved the successful handover probability by using the proposed optimum distance for handover triggering to initiate the handover process which is 98% of handover will be successful.

In order to fully exploit the potentials of the heterogeneous cloud radio access networks (H-CRANs), how to associate the user equipments (UEs) with the appropriate low power nodes (LPNs) is a very essential problem. However, when the fronthaul constraint is limited, the UEs are sensitive to delay, and the LPNs are concerned about the traffic balancing, such a problem has not gained enough attention. In this paper, the aforementioned user association problem is investigated and formulated as a bidirectional matching game, where the UEs are seeking to access the most preferred LPN while the LPNs are seeking to accept the most preferred UEs. To find the solution to the proposed game, an iteration algorithm is proposed, and its computational complexity and convergence are proved as well. Simulation results show that our proposed user association scheme is effective and outperforms the existing schemes-in terms of achieved data rates, delay, traffic balancing and overall utility.

The use of small cell deployments in heterogeneous network (HetNet) environments is expected to be a key feature of 4G networks and beyond, and essential for providing higher user throughput and cell-edge coverage. However, due to different coverage sizes of macro and pico base stations (BSs), such a paradigm shift introduces additional requirements and challenges in dense networks. Among these challenges is the handover performance of user equipment (UEs), which will be impacted especially when high velocity UEs traverse picocells. In this paper, we propose a coordination-based and context-aware mobility management (MM) procedure for small cell networks using tools from reinforcement learning. Here, macro and pico BSs jointly learn their long-term traffic loads and optimal cell range expansion, and schedule their UEs based on their velocities and historical rates (exchanged among tiers). The proposed approach is shown to not only outperform the classical MM in terms of UE throughput, but also to enable better fairness. In average, a gain of up to 80% is achieved for UE throughput, while the handover failure probability is reduced up to a factor of three by the proposed learning based MM approaches.

The rapid growth of traffic demands has posed challenges and difficulties on both the radio access networks (RANs) and the backhaul links. While heterogeneous networks (HetNets) are expected to offer diverse radio access capabilities and improve the transmission performance of user equipments (UEs) significantly through integrating various RANs efficiently, the backhaul links may still experience challenges in offering quality of service (QoS) guaranteed services to UEs. To tackle these problems, caching technology, more specifically, caching user contents at the infrastructures of different RANs is proposed as an effective approach. In this paper, we consider the joint user association and cache content placement problem in cache-enabled HetNets. Stressing the tradeoff between user download delay and caching cost, we introduce the concept of utility function which characterizes the joint network performance as the weighted sum of user download delay and the caching cost and formulate the joint user association and cache content placement problem as a network utility optimization problem. As the formulated optimization problem is a nonlinear integer optimization problem which cannot be solved conveniently using traditional optimization tools, we transform the original optimization problem equivalently into three convex subproblems by applying Lagrange partial relaxation and McCormick envelopes, and then propose an iterative algorithm. Within each iteration, for a given set of Lagrange multipliers, the three subproblems are solved respectively by means of the modified Kuhn-Munkres (K-M) algorithm and the locally optimal solutions can be obtained, based on which the Lagrange multipliers can be updated through applying subgradient method. Simulation results demonstrate the effectiveness of the proposed algorithm.

5G New Radio (NR) is the 3rd Generation Partnership Project (3GPP) radio access technology for the next generation mobile communications network. A major evolution of 5G constitutes the integration of non-terrestrial networks including geostationary and low Earth orbit satellites. The seamless integration of satellites in the terrestrial mobile network requires significant adaptations within the radio access network and the development of new features in the core network to cope with the specific satellite channel characteristics. To date, the 5G control and data plane has been standardized to handle only continuous backhaul communication between the network components. However, a mobile satellite enabled next generation Node B (gNB) located in a vehicle or in a moving aerial platform needs to be able to handle frequent backhaul outages of various duration as well as longer signal delays as opposed to short terrestrial connections via fiber. In this paper, we report the results of an over-the-air (OTA) field trial comprising a mobile edge node connected to the 5G standalone core network components over a geostationary satellite. We analyze Transmission Control Protocol (TCP) acceleration and GPRS Tunneling Protocol (GTP)/TCP/Internet Protocol (IP) header compression features through the GTP. Moreover, the influence of short and long interruptions in the communication between the edge node and the central components on the entire system performance is investigated. The header compression and TCP acceleration modules were implemented on the satellite modems and are now part of the protocol stack of these devices. The results show up to 12% higher data rates for the 5G user equipment (UE), on a 1.5 MHz single carrier return link compared to deactivated TCP acceleration and header compression. We increased the data rate by 20% on the 4.5 MHz DVB-S2X forward link between the UE and 5G core. Moreover, our measurements reveal that even satellite-enabled gNB mobility is possible with the current Release 15 standard. After a short outage of the satellite connection due to shadowing, the UE can successfully re-establish the user plane connection to the core network. Our results will facilitate the full integration of satellite components in 5G through open and standard solutions.