Cell Selection in 4G Cellular Networks

In this chapter, a brief overview of the role and applications of machine learning (ML) algorithms in future wireless cellular networks is presented, more specifically, in the context of self-organizing networks (SONs). SON is a promising and innovative concept, in which future networks are expected to analyze and use historical data in order to improve and adapt themselves to the network conditions. For this to be possible, however, algorithms that are capable of extracting patterns from data and learn from previous actions are necessary. This chapter highlights the utilization and possible applications of ML algorithms in future cellular networks. A brief introduction of ML and SON is presented, followed by an analysis of current state of the art solutions involving ML in SON. Lastly, guidelines on the utilization of intelligent algorithms in SON and future research trends in the area are highlighted and conclusions are drawn.

Future cellular networks are expected to provide significantly higher capacity than today's systems. To support this higher capacity a denser deployment might be necessary. An alternative way is to deploy Multiple-Input-Multiple-Output (MIMO) base stations (BSs), called advanced BSs, so that the system capacity is improved without increasing the BSs density. This paper compares Single-Input-Single-Output (SISO) BS deployments with MIMO BS deployments from a cost perspective. We use a deployment methodology starting with a sparse density of BSs. By deploying additional BSs sequentially the number of BSs is increased until the traffic demand in the network area is supported. Providing equal service level, i.e., supporting the same traffic demand, by means of different deployment realizations enables a relevant comparison between the alternative single and multiple antenna systems. With the models and assumptions used here, results show that in order to support the same users' service level, the cost of deploying MIMO BSs is significantly less compared to increasing the density of SISO BSs. The cost gain is due to the reducing of the number of required BSs for the case of MIMO deployment.

The aim of this paper is to introduce a novel frequency reuse concept especially for macro cellular networks to substantially increase mobile network capacity, and simultaneously to avoid the implementation of low efficient small cells. Single path multiple access (SPMA) utilizes the characteristics of independent propagation paths for particular geographical location in the coverage area of mobile network. In SPMA concept, a communication between base station and mobile station happens through single independent propagation path, and the frequency resources can be reused in 5m × 5m areas, or even more often in 1m × 1m areas. Thus, the capacity of the network will be increased dramatically, and it can be managed in centralized manner at certain macro site locations. In already deployed cellular networks, these macro sites are mostly easily available, and that would help to implement SPMA to enhance the network capacity. Simulation results provided in this paper show the applicability of single path multiple access technique, by limiting the radiation of signal as single path propagation between base station and mobile station.

Future cellular networks are expected to provide significantly higher capacity than today's systems. This might require a denser access point deployment, with a potential increase in network deployment cost as a consequence. A promising way to reduce cost is a multi-hop deployment where wireless relay nodes (RN) are introduced to enhance capacity and coverage. In this paper, a deployment procedure for a static radio environment is considered, adding RNs incrementally as a complement to initially deployed macro base stations (BS). Different strategies of deploying BSs and RNs, providing equal service levels, are analyzed from a cost perspective. We develop a methodology that can determine and compare the most cost efficient deployment mixes of BSs and RNs. Further, we compare a deployment of macro BSs and relays with a deployment of macro BSs and micro BSs. Results show that relays are more cost efficient if the micro BS cost is between 10 and 15 % higher compared to the cost of an RN.

Rapid growing demand for mobile data traffic challenges capacities and service provision in the next-generation (5G) cellular networks. Real measurement data from operating cellular networks indicates that the traffic models and scenarios disobey our traditional assumptions (i.e., expressing bursty nature). As a result, current network architectures and service management may cause experience deterioration of subscribers in future networks. In this article, we propose three approaches to alleviate the influence of various traffic bursts: baseband resource pool on a cloud platform as wireless infrastructure to enhance the capacity and flexibility of networks, cloud core networks to provide dynamic extension and service flow control abilities, and software-defined bearer networks to simplify service delivery instructed by core networks. Different from conventional stovepipe-like cloud computing network architectures, our proposed architecture interconnects and shares information between entities, breaking through horizontal device barriers and vertical layers. These cloud-based approaches not only avoid the potentially negative impact of bursts, but also provide a software-controlled end-to-end service management framework for future cellular networks. In addition, by taking advantage of open interfaces of cloud-based network elements, service control algorithms and network APIs could also be implemented to realize smart and soft 5G cellular networks.

In traditional cellular networks with fixed base stations, the channel reuse pattern is static and deterministic. When the cell layout is dynamic, due to the mobility of base stations, the cluster of cells within cochannel interference range changes with time. Consequently, the channel reuse pattern is highly dynamic. Moreover, base stations also need wireless channels to communicate amongst themselves. A communication session between a pair of nodes may have to switch channels due to the movement of other nodes into the neighborhood. None of the existing dynamic channel allocation algorithms for cellular networks works in such a system. Hence, there is a need for new wireless channel allocation algorithms for virtual cellular networks with mobile base stations. In this paper, principles of mutual exclusion pertaining to distributed computing systems are employed to develop such an algorithm. The inter-base-station wireless links are referred to as backbone links, while the base station to mobile node links are referred to as short-hop links. The proposed algorithm is distributed, dynamic, and deadlock-free. Disjoint sets of channels are used for backbone and short-hop links. The distributed nature of the channel allocation scheme leads to scalability and robustness, as the responsibility is no longer centralized at the mobile telecommunications switching office (MTSO). Instead, it is shared among all the mobile base stations. In addition, the issue of channel rearrangement is addressed. Channel rearrangement is the switching of channels, performed to prevent cochannel interference, when mobile base stations using the same channels, hitherto not in interference range, come within the range of each other. If multiple channels are available to support a communication session, the channel selection policy can have a significant impact on performance. A random selection from the set of available channels yields better performance at low to moderate channel demand. This is in contrast to ordered channel selection (from one end of the spectrum), which always yields the best performance for cellular networks. Results obtained by simulating the algorithm are consistent with the theoretically obtained values.

Achieving maximum network throughput while providing fairness is one of the key challenges in wireless cellular networks. This goal is typically met when the load of base stations (BSs) is balanced. In a recent study, it was confirmed that the preamble sequence, which is mainly used for cell identification and synchronization, can be used as an implicit load indicator for long term load balancing in cellular networks. In this paper, we further explore its viability as an implicit information indicator, and present distributed load balancing schemes based on the properties of the preamble sequence. These schemes empower the mobile stations (MSs) to implicitly obtain information about the load status of BSs for intelligent cell-site selection. By utilizing the two characteristic and important properties of preamble sequences, which are high auto-correlation and low cross-correlation, we propose both network and user side algorithms that work together to enable the MSs to associate with BSs with relatively low load in the long term. We evaluate our algorithms for fairness to the MSs in terms of resources and throughput, and confirm through simulations that the preamble sequence can indeed be used as a leverage for better cell-site selection leading to a high degree of fairness in the system.

Cellular networking has entered the paradigm of next generation networking, Software Defined Mobile Networking (SDMN) and Cloud Radio Access Networks (CRAN). This paradigm shift has compelled to improve future cellular networks by making them more efficient and smart. The improved, future cellular networks could have a profound impact on the commercial and research segments in terms of capital expenditure and operational expenditure by presenting a unified robust technology for data connectivity. In future, 5G cellular networks will be progressed with LTE that will facilitate this technological transformation. Future 5G demands reliance on more flexible and dynamic technologies such as static Radio Access Networks (RAN), otherwise resources will be depleting and will be unable to meet the surging demands including wireless transmission connectivity and providing an efficient network bandwidth. To address this problem, the paper presents a study exploring the amalgamation of Software Defined Network (SDN) and cloud computing achieve Cloud RAN or RAN-as-a-Service (RANaaS). This helps to overcome the problems associated with handling enormous matrix of connecting devices and nodes. This paper explores existing research geared towards the deployment of 5G networks through Remote Radio Heads (RRH) and Virtual Base Stations (VBSs) backed by SDN. Furthermore, this research survey is an effort to unearth the security implications and challenges of CRAN while adopting LTE and SDMN services in CRAN based 5G networks. The security challenges of conventional wireless networks are framed to emphasize on the need to migrate from traditional RAN to CRAN. Subsequently the possible mitigation techniques are also discussed. Furthermore, the role of SDN and its security artifacts are also explored to embed security within the CRAN architecture.

Positioning functions, which are automatic positioning of subscribers within cellular networks, are required for mobile communication systems of all generations. However, when new generation networks are implemented, high accuracy of determining mobile station geographical coordinates is required for development of services related to subscribers’ location. To solve the task of mobile station positioning its geographical coordinates are calculated in regard to the known coordinates of base stations. The paper proposes to use a neural network for improving the effectiveness of positioning a mobile station of a cellular communication system. Positioning methods providing usage of neural networks are based on measurements of levels for signals from base stations whose coordinates are known or all the nearest access points. After creating a software or hardware solution for the artificial neural network, one has to create a mathematical model for positioning and perform the network training procedure. The proposed localization method is based on RSSI values. The advantage of the RSSI method is that it requires no additional hardware or computing power. The disadvantage of the RSSI method is the lack of accuracy. Thus, the aim of this paper is to develop an optimized method for determining mobile station location. According to the proposed method, RSSI values ​​from several (at least three) closest base stations to a mobile station enter the neural network, after corresponding processing; the coordinates (latitude and longitude) of the mobile station appear at two outputs. The proposed neural network is a multilayer perceptron. The article presents the proposed architecture of the perceptron. The number of neurons in all the layers has been substantiated. The operation of the multilayered perceptron has been described.

In this paper, we study the degrees of freedom (DoF) of cellular networks in which a base station with full-duplex operation simultaneously communicates to multiple half-duplex mobile stations. The half-duplex mobile stations are assumed to either communicate with the base station in the uplink or downlink. For such networks, inter-terminal interference needs to be taken into account to achieve the potential gain that doubles the throughput of conventional half-duplex cellular networks. We provide an achievable total DoF for such networks and show that having full-duplex operation at the base station only can indeed double the DoF when the number of mobile stations is sufficiently greater than the number of antennas at the base station. The key idea is to utilize the full DoF for the uplink transmission, while minimizing the inter-terminal interference via interference alignment. The downlink communication rate is then carefully chosen to occupy the remaining DoF at the receiving mobile stations.

Orthogonal frequency division multiplexing (OFDM) has been widely regarded as an effective modulation technique for mitigating the effects of ISI in a frequency selective fading channel and for providing reliable high data rate transmission over wireless links. Adaptive antenna arrays at the base and mobile stations can achieve further increases in system's capacity and bandwidth efficiency, as well as in QoS improvement in conventional OFDM systems. The conventional adaptive antenna arrays based OFDM systems always use the sub-carriers characterized by the first largest eigenvalues to transmit the OFDM block symbols. In this paper and in contrast to previous work, we propose dynamic sub-channel allocation with adaptive beamforming for broadband OFDM wireless transmission systems. The proposed system adaptively selects the eigenvectors associated with the relatively large sub-channel eigenvalues to generate the beamforming weights at the mobile and base stations and then dynamically assigns the corresponding best sub-channels to transmit the OFDM block symbols. It is shown by simulation that, without adding much complexity, the proposed system can achieve a better performance than an adaptive antenna arrays based OFDM system without dynamic sub-channel allocation over multipath fading channels. Simulation results also reveal that the proposed system is not too sensitive to channel estimation errors.

As for radio channel control of a cellular mobile communication system, location measurement is an important technique for determining the base station to be Connected with the mobile station. This paper describes the radio zone selection characteristic when a part of the control channel is time‐shared by base stations and the reception level of each base station is measured at mobile stations. MSSC (Multitransmitter Simul/Sequential Casting) of control channels is proposed, which improves the location measurement and is suitable for a high‐capacity system. The MSSC channel consists of simul‐cast parts and sequential‐cast parts. Its speech connection control sequence when applied to the cellular mobile communication system is shown. Next, the relation between the reception level variation characteristic in land mobile communication and the average reception level measurement accuracy when burst signals are received several times is studied. Both analytical results and laboratory experimental simulation results are shown. Finally, the zone selecting rate of a mobile station is calculated and the effect of the proposed control channel configuration is clarified.

Network base station (BS) requires specific measurement reports from mobile station (MS) user equipment for MS localization in 3GPP cellular network. Multiple techniques have implemented at Network side with a performance of the localization, while MS-based localization is inadequate. This paper proposed a method for an MS to estimate BS and MS location based on received signal strength (RSS) and received signal quality (RSQ) in 3GPP UMTS cellular network. Suitable approximations used and formulate the localization problem based on Long-distance Path Loss model with consideration of signal strength and signal quality affected by noise and interference. Simulation results show a promising performance for the proposed method, is the solely MS-based method.

It is well known that Multiple-Input Multiple-Output (MIMO) system provides both spatial and diversity gains by using multiple antennas at both mobile and base stations. However, the mobile station cannot effort multiple antennas due to small and limited dimension. Therefore, the MIMO technique cannot be successfully operated. In this light, the cooperative MIMO technique enables a mobile user with single antenna to realize a virtual multiple antennas by using the antennas of neighboring users. As a result, the mobile user can experience the full benefits of MIMO system. In literatures, the cooperative MIMO technique using Space-Time Block Codes (STBC) is created by the relay capability of neighbor users. However, the devices of all users have the same potential to detect symbols. Therefore, this paper proposes the STBC scheme by changing the symbol order from source to relay in order to be easily performed as MIMO at the destination. The simulation results reveal that it is possible to obtain a better error performance as well as a higher channel capacity by using the proposed scheme for mobile cellular networks.

The Internet protocol (IP) can potentially become the universal network-layer protocol over all wireless systems as it already is for wireline packet networks. Such an all-IP wireless and wireline network can bring the proven advantages of IP networking to mobile users. However, realizing an all-IP wireless network introduces many challenges, among which is soft handoff. Two major problems need to be solved in order to support soft handoff. First, multiple streams of the same IP traffic have to be distributed via multiple base stations to a mobile station. Second, pieces of data arriving at the mobile station at the same time from different base stations need to be copies of the same data in order for the mobile station's radio system to correctly combine these different pieces into a single copy. A similar problem also needs to be resolved in the reverse direction from mobile stations to base stations. Solving these problems in a distributed all-IP wireless network remains a challenge. Although solutions exist for today's circuit-switched wireless systems. This article presents a new approach for soft handoff in distributed all-IP wireless networks. It consists of two main parts. First, a new design of IP-based distributed base stations enables mobile stations in multiple cells to be on the same IP subnet and multiple streams of the same data to be distributed via multiple base stations to a mobile without broadcasting/multicasting and with minimal signaling. Second, a novel IP-layer procedure performed by the base stations ensures that the data coming simultaneously from multiple base stations to a mobile station are copies of the same data.