Mobile Networks Tracking
In their research, Ficek, Pop, and Kencl (2013) state that the tracking of mobile networks and mobile terminals within the former are the two approaches that are growing in a progression and are being applied in diverse settings. Nonetheless, the researchers believe that numerous implications are inherent in this task and its inconsequential nature may become the reason for serious adjustments in the network and cooperation patterns (Ficek, Pop & Kencl 2013). The investigation of the tracking aspect of mobile networks showed that the majority of mobile operators are keen on applying flexible and profitable techniques of network-based tracking. In this research, Ficek, Pop, and Kencl (2013) conduct extensive research on active mobile tracking based on SMS technology. The researchers have chosen this method intending to demonstrate that this discreet approach can be employed in the majority of the current mobile network architectures (Ficek, Pop & Kencl 2013). The key finding of the study consists in the fact that the efficiency of this method is proved and the results of the experiment show that the SMS-based tracking technology allows the system to track thousands of mobile network subscribers within the time frame of several minutes. In conclusion, the authors of the research provide their opinion concerning the active tracking methodology and its limitations (Ficek, Pop & Kencl 2013). Moreover, they discuss the applicability of the reviewed methodology, its long-term efficiency, and terminal constraints that are inherent in the design of this methodology (for instance, mobile network capacity).
Another study in the area was conducted by Xu, Ding, and Dasgupta (2013) and featured the review of the mobile sensors and the problem of tracking the mobile devices that emit the signal. In other words, the researchers were concentrated on exploring the nature of signal reception and the problem of unexploited mobile targets (Xu, Ding & Dasgupta 2013). The researchers also specify that the mobile sensor has to utilize a special controller when the maneuvers of the target are unknown or unpredictable. This is done in order to collect the data offered by the network functioning on the basis of a wireless sensor (Xu, Ding & Dasgupta 2013). This approach is heavily dependent on the time of arrival of the signal. As the researchers explain, the measurement of the information concerning the signal’s time of arrival is obtained by means of the mobile sensor. After that, the system locates the mobile sensor and orders it to follow the initial target (Xu, Ding & Dasgupta 2013). The researchers apply an approach that features an approximation of minimum and maximum values so as to evaluate the location for tracking. As a consequence, they take advantage of the mobile sensor navigation and utilize a cubic function. One of the main findings of the study is that the tracking accuracy can be achieved by the joint estimation of the location of both the target and the mobile sensor (Xu, Ding & Dasgupta 2013). Additionally, the authors of the research find the way to apply a subjective tracking algorithm that is expected to improve the efficiency of the tracking system by utilizing the obtained measurement data in a competent manner. The outcomes of the study show that the performance of the location services increases dramatically and the sensor can be directed promptly to follow the mobile target (Xu, Ding & Dasgupta 2013).
Long Term Evolution (LTE)
In his 2015 research, Jover explored the implications of one of the latest standards in mobile networks. This standard is called Long Term Evolution (LTE), and it is available all over the world as it provides stable connectivity and allows any individual to access numerous extra services offered to the owners of mobile devices (Jover 2015). Furthermore, the LTE technology is considered to be one of the essential parts of the Machine to Machine systems aimed to provide worldwide communication and implement the service called Internet of Things. The author of the research explicitly states that security of the network is one of the critical aspects of the LTE networks due to their extended functionality and a large number of subscribers (Jover 2015). The mobile communications system that was popular back in the day (GSM) is now considered insecure in comparison to the LTE networks as it was susceptible to reprobate base stations. LTE, on the other hand, is called the future of the mobile communication systems as it offers confidentiality to all subscribers (Jover 2015). Nonetheless, it turned out to be partially incorrect due to the fact that the weak point of the LTE networks was its inability to neutralize security threats that interfered with the accessibility, confidentiality, and certification. In this paper, Jover (2015) investigates the issues connected to the security aspect of LTE networks and summarises the existing evidence concerning protocol exploits. The author discusses the results of the employment of LTE networks and their vulnerability (Jover 2015). The researcher also examines the key aspects of IMSI catchers and potential threats that may lead to the locking of a mobile device. In this paper, Jover (2015) discusses the ways to mitigate the adverse outcomes of using LTE networks and focuses on a previously unknown methodology of tracking a mobile device and its location.
In 2012, Peral-Rosado et al. investigated the implications of the Global Navigation Satellite System (GNSS) and its appearance on the market. The receivers that were used in cell phones were contingent on numerous working conditions (Peral-Rosado et al. 2012). The authors discussed the possibility of utilizing mobile terminals both indoors and outdoors. They were able to compare the results of operating GNSS in both rural and urban settings and came to the conclusion that the robustness of the system is the most important factor affecting the process of locating the mobile device or any other device connected to the network (Peral-Rosado et al. 2012). The authors of the research also stated that GNSS receivers have to be used in numerous challenging settings. Therefore, the enhancement of the quality and robustness of these devices is critical, but performance remains one of the core weaknesses of this technology despite the extensive research in the area (Peral-Rosado et al. 2012). Taking this into consideration, the authors were able to reach a verdict concerning the utilization of GNSS systems. Ultimately, the performance of these location systems could be increased by means of the complementary systems. In other words, the GNSS worked better in combination with the exclusive data provided by an external source (Peral-Rosado et al. 2012). In any setting, the GNSS system could rely on inertial navigation systems or cellular networks. In addition to that, there were several other alternative methods based on the utilization of signals of opportunity and their hybridization. Nonetheless, one of the key findings of the study was that the LTE technology critically improved the strength of the GNSS performance (Peral-Rosado et al. 2012). As the authors of the study explain, the particularities of the LTE technology are employed for positioning purposes. In their research, Peral-Rosado et al. (2012) concentrate on the accuracy of the localization services and present a number of scenarios where the LTE services are used to improve the robustness of the GNSS technology. They take into consideration the delay estimation time with the intention of evaluating the positioning eminence of the LTE technology.
In their research on the principles of LTE detection and positioning, Peral-Rosado et al. (2015) state that vertical positioning is one of the crucial topics that should be reviewed by the specialists in the area due to the fact that this technology is rather effective in indoor settings. Moreover, the researchers emphasize the importance of complying with the strict requirements of E911 and its connection to the location accuracy in indoor environments (Peral-Rosado et al. 2015). Taking this into account, the researchers investigated the implications of floor detection and the application of indoor positioning practices that satisfy the requirements of the legal directives. Peral-Rosado et al. (2015) found that the implementation of the LTE networks allowed to make the best of their heterogeneous nature and resolve the issue of poor positioning due to the amalgamation of the positioning capabilities of the LTE technology and its focus on the communication services. Overall, the authors of the paper provide the readers with an extensive overview of the currently existing LTE detection methods (Peral-Rosado et al. 2015). The investigators also completed a test that included the use of the GNSS and an experimental LTE network. The testing was performed at the site that featured a two-story building and inertial sensors. The results of the study showed that the chance of floor detection increased by more than 65% and there were a number of positioning resolutions that could be applied in that setting (Peral-Rosado et al. 2015).
The study that was conducted by Wu et al. (2014) concentrated on the output of the existing 4G LTE networks. The researchers consider this technology to be one of the key features of the next-generation cellular networks and expect that the networks based on the 3GPP will serve as the perfect ground for the development of 4G networks (Wu et al. 2014). The researchers apply their knowledge of the cellular network design to detect the possible ways of increasing the performance of the network and enabling high-probability data detection approaches. The key idea of the research is that there is a possibility to reduce the intricacy of data detection by means of a novel algorithm that is based on the expansion of the ideas proposed by Neumann (Wu et al. 2014). The researchers present a comparison to the readers that features the analysis of the associated errors and their contingency on the involvedness of particular linear detectors. The authors of the paper are basing their investigation on the currently available architectures that perform data detection under a variety of circumstances and antenna configurations (Wu et al. 2014). The results of the experiment showed that there is a possibility to achieve over 600 Mb/s by means of a 128 antenna and a 3GPP system based on LTE technology. In the final section of the paper, the researchers compare the findings in terms of the performance and intricacy of the network design (Wu et al. 2014).
Another important aspect of LTE networks is the efficiency of geolocation. The research conducted by Jarvis, McEachen, and Loomis (2011) discovered the geolocation prospects inherent in the LTE networks and connected these possibilities to the timing intervals and several other ranging parameters. The subscriber stations were thoroughly evaluated and the overall internal effectiveness of geolocation (Jarvis, McEachen & Loomis 2011). The researchers present to the reader the approach that is based on the distances from various base stations. It is also important to note that the calculation of these distances is dependent on the particulars of the LTE timing parameters. The researchers applied a nonconventional mapping system and computer simulation to conduct the experiment. The test also involved several base station networks and was utilized to validate the accuracy of geolocation services (Jarvis, McEachen & Loomis 2011). In addition to that, the researchers further revised the computer simulation so as to display the accuracy of geolocation services on a three-dimensional mapping system. They were able to estimate the probable locations of subscriber stations. The key finding of the study states that a two-dimensional mapping scheme can be efficiently used to improve the accuracy of geolocation (Jarvis, McEachen & Loomis 2011). The involvement of the timing advance method positively impacted the outcomes of the experiment and exceeded the results obtained throughout the previous studies conducted by other researchers. The findings concerning the three-dimensional mapping system showed that the accuracy of geolocation could be improved up to the limit of 50 centimeters (Jarvis, McEachen & Loomis 2011).
The issues of LTE geolocation were also investigated by Roth, Tummala, and Scrofani (2016) as they explored the weaknesses of the existing cellular networks. They found that the location-based attacks represented one of the biggest threats to the networks and considered the impact of uplink timing supervision. On a bigger scale, the researchers were able to extend the knowledge concerning the security issues inherent in the GSM networks and provide additional evidence related to the LTE networks (Roth, Tummala & Scrofani 2016). Nonetheless, the researchers also state that the appearance of the heterogeneous 4G networks turned out to be not so successful due to the development of attacks that were triggered by the increase in the demand for data output. Numerous vulnerabilities of the LTE networks were exposed by these attacks (Roth, Tummala & Scrofani 2016). The researchers present a novel approach based on the idea of leveraging an available LTE network to synchronize the cellular network and uplink timing. This passive method allowed the authors of the study to improve the efficiency of the commands distributed by the network (Roth, Tummala & Scrofani 2016). The findings of the study state that the developed approach may be useful not only in LTE networks but legacy deployments as well.
In 2014, Peral-Rosado explored the capabilities of the signals coming from the multicarrier systems. These signals are characterized by condensed multipath and the efficiency of cellular networks in strict environments (Peral-Rosado 2014). Therefore, the author of the study applies the LTE standard within the framework of this research. The importance of the LTE standard can be explained by its support of a multicarrier format named orthogonal frequency-division multiplexing. Moreover, this format signifies the downlink transmission that is characteristic of the LTE networks (Peral-Rosado 2014). The positioning technique based on the time difference of arrival is also taken into consideration as the LTE identifies the signals coming from the multicarrier. In turn, the latter is calculated on the basis of the estimations of the ranges (that are in compliance with the nearest base stations). Mobile devices of the subscribers can be located by means of defining the positioning reference signal and estimating the delay of the signal (Peral-Rosado 2014). In this research, the author dwells on the capabilities of the LTE networks in terms of efficient localization by means of the positioning reference signal. The study is focused on the provision of multipath and inter-cell interference as these are the two key deficiencies of the LTE networks.
The time difference of arrival is also thoroughly assessed in Zhang et al.’s research (2012) as they consider it to be one of the core positioning methods utilized in 3GPP. The researchers also review this network and compare the specifications of the 3GPP to the peculiarities of the advanced LTE. The key objective of this study was to identify the most influential drawbacks of the conservative method of calculating the time difference (Zhang et al. 2012). The researchers were also interested in studying the scenarios that might transpire during the process of operating a heterogeneous 4G network. As a result, the authors of the study provide the readers with the solution of the problem that features two different schemes (multiplexes) utilized to process the positioning reference signal – a time division and a code division (Zhang et al. 2012). The outcomes of the experiment exceeded the researchers’ expectations as they were able to improve the positioning accuracy by utilizing the proposed method which is in full compliance with the requirements of the federal commission dealing with communications.
The research conducted by Fischer (2014) also reviews the functional capabilities of the time difference of arrival in LTE networks and compares the results to the 3GPP networks (Fischer 2014). The author of the paper provides an extensive overview of the features inherent in both types of cellular networks and provides a number of critical details that would be useful for cellular operators. Overall, the researcher was able to describe the procedures related to the time difference of arrival and various signals transferred by means of the 3GPP network (Fischer 2014). He also discusses the perfect circumstances necessary to deploy a 3GPP network successfully. A number of location principles are described by the researcher and several examples of time difference measurements are presented to the readers (Fischer 2014). The author of the paper also provides a detailed summary of how the position reference signal works within the framework of the 3GPP network. Fischer (2014) explains that this important factor cannot be controlled by the vendors and operators (for instance, an environment that involves radio propagation). Nonetheless, the researcher states that other aspects of the network can be controlled and successfully deployed to support the time difference feature.
LTE Collaborative Positioning
The study conducted by Vaghefi and Buehrer (2014) features a detailed review of collaborative positioning in LTE networks. The purpose of the study can be explained by the relevance of location-based services and E911. The GNSS is identified by the researchers as the most effective positioning system that is available to the subscribers of all the cellular networks. Nonetheless, the authors of the paper indicate that there are limitations (for instance, poor indoor performance) that identify the positioning services as a backup method in the majority of the cases (Vaghefi & Buehrer 2014). During the implementation of the cellular localization, no external sources are utilized to collect the measurements responsible for the user’s location data. The authors highlight the efficiency of the positioning technique based on the time difference of arrival methodology that is an essential part of the 3GPP LTE network. Vaghefi and Buehrer (2014) describe the algorithm and the requirements that should be followed if it is necessary to locate the user. They also state that the current 3GPP LTE network setup is set to obtain the measurements, but it cannot connect to a satisfactory number of LTE networks and find the location of the cell phone without indistinctness. The authors of the paper describe a novel technique of localization for the LTE networks that connect to both other LTE networks and other user’s equipment (Vaghefi & Buehrer 2014). So as to show the advantages of this method, the researchers conducted a series of virtual simulations where they utilized collaborative localization and set all the necessary parameters for the 3GPP network.
Another research conducted by Vaghefi and Buehrer (2015) dwelled on the idea of using radio frequencies in the environments that presuppose collaborative positioning within LTE cellular systems. The authors of the study explain that the network-based solutions are developed in an attempt to improve the performance of GPS service in indoor and impenetrable environments (Vaghefi & Buehrer 2015). The idea of cellular localization is further supported in this paper, and this feature can be implemented without the use of GPS or any other similar services. The significance of user equipment is connected to the difference of incoming signals and probability of finding its location. Nonetheless, the use of a multipath approach can gradually decrease the performance of this localization method (Vaghefi & Buehrer 2015). This is why the strategies that involve the use of radio frequencies are currently applied by numerous companies and studied by the researchers. It has been proven that the methods that involve the use of radio frequencies tend to show good performance scores in impenetrable urban areas and indoor environments. The idea of collaborative positioning in LTE networks is proposed in this paper. The methodology includes the communication technique called Device-to-Device and allows the user equipment to transfer the data to all destinations (Vaghefi & Buehrer 2015). The high level of performance is proven by a number of computer simulations based on the proposed positioning algorithm.
The research conducted by Mumtaz et al. (2012) dwells on the efficient management of the radio resources available within the wireless network systems. The authors of the study state the increasing necessity of implementing changes into practice due to the constantly increasing number of subscribers and development of applications that require a high-speed connection. The researchers focus on the two key concepts – collaborative positioning in LTE and radio resource management based on the localization methods (Mumtaz et al. 2012). The objective of the study was to come up with a sole entity that would be in charge of handling the radio resources within the 4G environments. The authors of the paper state that the use of collaborative positioning significantly increased system performance and allowed to optimize the overall functioning scheme. The positioning information was used to enhance the performance of LTE networks and investigate the distinctive aspects of the approach (Mumtaz et al. 2012). The optimization of the environment helped the researchers to reach the verdict concerning the use of the positioning information and boost the performance of the existing system.
In their research, He, Ma, and Tafazolli (2012) reviewed a novel collaborative positioning approach that utilized the multiple access systems built on the basis of the orthogonal frequency-division method. The idea of this approach consists in the fact that idle mobile terminals could be used to estimate the time of arrival with the intention of synchronizing with the active mobile terminals (He, Ma & Tafazolli 2012). The key advantage of the approach found by the investigators was that it did not require any extra measurements to be made by the mobile terminals. Furthermore, the positioning accuracy of the developed method was expected to improve the current results. The findings of the study show that the use of mobile terminals is also an important asset for the collaborative positioning approach that improves the accuracy of localization and eliminates time bias among the idle mobile terminals (He, Ma & Tafazolli 2012).
LTE Test Challenges
The research by Thorpe (2012) discusses the issues that appeared with the development of the LTE networks and their requirements. The author of the paper points out the increase in the complexity of the network and the necessity to sustain a large number of location technologies and proprieties that are present in the users’ devices (Thorpe 2012). This level of complexity triggers the need to perform numerous tests and guarantee that all the devices within the network will function better after the deployment of a variety of commercial tools. Nonetheless, the real level of performance cannot be evaluated due to the inability to create ideal GNSS and cellular conditions (Thorpe 2012). The author of the study dwells on the importance of testing different scenarios and performing standard assessments aimed to evaluate antennas and receivers in addition to the accuracy of the measurements. Real-world conditions set limitations in terms of a number of conditions and impact the protocol transfer reliability (Thorpe 2012). Numerous networks encounter the issues of inaccurate design, poor backward compatibility, and a high level of complexity. All these challenges greatly impact the costs of the network and its flexibility. Even though the majority of the tests rise above the minimum requirements, the test methodology proposed by the researcher features a comprehensive set of tests that should be performed to fully assess the performance of a network (Thorpe 2012). Overall, the study develops a number of ideas concerning the tests that should be performed to evaluate the challenges characteristic of the 3GPP LTE networks and lists the solutions aimed to improve the efficiency of the 4G services.
The research conducted by Elmokashfi (2015) is grounded on the data collected from the fake base station. The two key sources of the data utilized by the researcher are Aftenposten and Delma, and the obtained data indicate that the fake base station was active in Oslo during the year 2014 (Elmokashfi 2015). The measurements obtained by the author of the research can be split into several groups. Delma is represented by two groups. First, the findings include the alarms that are functioning in compliance with the default GSM networks in Norway. These discoveries also include provider anomalies and short-lived cells (Elmokashfi 2015). The number of false alarms could be significantly reduced if the mobile operators realized the proper configuration of cellular networks in Norway. Second, the findings include the fake base station and LAC anomalies. This particular group is based on the measurement data concerning the irregularities inherent in the cellular networks due to the existence of fake base stations (Elmokashfi 2015). Nonetheless, the author of the study supposes that these irregularities can be explained by the unbalanced behavior of the equipment utilized to measure the data. The discoveries based on the data provided by Aftenposten showed that the alarms were reliant on the crypto phone measurements. In this case, the alarms did not include any data activity but involved certain unsanctioned activity on the radio frequencies (Elmokashfi 2015). The researcher presupposes that this activity is within the norms of user equipment functionality. The core conclusion of the study is that the measurements reviewed throughout the study are not sufficient to exclude the likelihood of fake base stations’ existence, but there is not enough evidence to prove it as well.
The research conducted by Dabrowski et al. (2014) focuses on the key methods of identifying the artifacts produced by the mobile networks. The authors of the study developed several approaches that involve the use of an IMSI catcher intended to safeguard the privacy of the subscribers (Dabrowski et al. 2014). The first approach utilizes the stationary measurement units so as to scan the available frequency bands within the designated geographical area. This is necessary to identify all of the announcements with a cellular network and save the initial parameters set by the cell network. This approach can function on a rather large area (Dabrowski et al. 2014). The second approach is the development of an application that will not require the users to jailbreak their phones. This approach is functioning on the basis of the correlations inherent in the topology of the cellular network and the GPS receiver that is incorporated into modern mobile devices (Dabrowski et al. 2014). The function that that reads the initial parameters of the network matches the learned data to the cell landscape. Both of the solutions were implemented and tested by the researchers with the object of identifying the ways to guarantee the digital defense on a long-term basis.
Mobile Edge Computing
In their research, Hoymann et al. (2012) thoroughly investigate the subject of mobile computing. They state that the transformation of the market and the shift towards the centralized mobile edge computing can be explained by the development of 5G communications and fade of the cloud computing. The core feature of this approach supposes that such aspects of the computing as mobile devices, network controllers, and storage policies will be moved to the network edges (Hoymann et al. 2012). This should be done in order to be able to develop intensive applications that comply with the critical aspects of latency and limited resources inherent in the majority of the mobile devices. The 5G vision serves as the base for the mobile edge computing which, in turn, promises significant decrease in latency and energy consumption (Hoymann et al. 2012). As the author of the research states, the prospects of mobile edge computing motivate the industry and technology to collaborate and modernize the current practice. Hoymann et al. (2012) focus on the survey intended to find the answers concerning resource management within the framework of mobile edge computing. The researchers also enumerate several scenarios that may be helpful for the specialists aiming to standardize the mobile edge computing development efforts.
Moreover, the research conducted by Jararweh et al. (2016) extends the existing knowledge and dwells on the mobile cloud computing services that are currently offered to the users of cellular phones. They see the limitations of the Cloudlet system as one of the key obstacles on the way to achieving the objective and gradually switching to mobile edge computing (Jararweh et al. 2016). Therefore, the emerging system serves as the gap-filling instrument and provides the resources that are necessary to deploy the 5G vision accompanied by mobile edge computing. The authors of the study present a hierarchical model that is composed of some Cloudlets substructures and mobile edge computing servers. The purpose of this model is to provide the cell phone users with an extended area of coverage and make all the services available while increasing the cost-effectiveness (Jararweh et al. 2016).
Dabrowski, A, Pianta, N, Klepp, T, Mulazzani, M & Weippl, E 2014, ‘IMSI – catch me if you can’, Computer Security Applications, vol. 4, no. 1, pp. 246-255.
Elmokashfi, A 2015, ‘An investigation into the claims of IMSI catchers use in Oslo in late 2014’, Resilient Networks and Applications, vol. 4, no. 1, pp. 1-17.
Ficek, M, Pop, T & Kencl, L 2013, ‘Active tracking in mobile networks: an in-depth view’, Computer Networks, vol. 57, no. 9, pp. 1936-1954.
Fischer, S 2014, ‘Observed time difference of arrival (OTDOA) positioning in 3GPP LTE’, Qualcomm Technologies, vol. 1, no. 1, pp. 1-62.
He, Z, Ma, Y & Tafazolli, R 2012, ‘Opportunistic Cooperative Positioning in OFDMA Systems’, Electronics, Communications and Computer Sciences, vol. 95, no. 9, pp. 1642-1645.
Hoymann, C, Chen, W, Montojo, J, Golitschek, A, Koutsimanis, C & Shen, X 2012, ‘Relaying operation in 3GPP LTE: challenges and solutions’, IEEE Communications Magazine, vol. 50, no. 2, pp. 156-162.
Jararweh, Y, Doulat, A, Alqudah, O, Ahmed, E, Al-Ayyoub, M & Benkhelifa, E 2016, ‘The future of mobile cloud computing: integrating cloudlets and mobile edge computing’, Telecommunications (ICT), vol. 1, no. 1, pp. 223-239.
Jarvis, L, McEachen, J & Loomis, H 2011, ‘Geolocation of LTE subscriber stations based on the timing advance ranging parameter’, Military Communications, vol. 1, no. 1, pp. 3-100.
Jover, R 2015, ‘LTE security, protocol exploits and location tracking experimentation with low-cost software radio’, Bloomberg LP, vol. 3, no. 1, pp. 1-9.
Mumtaz, S, Monteiro, V, Rodriguez, J & Politis, C 2012, ‘Positioning for performance enhancement in shared LTE and HSPA networks’, Telecommunications and Multimedia (TEMU), vol., no. 1, pp. 45-53.
Peral-Rosado, J 2014, ‘Evaluation of the LTE positioning capabilities in realistic navigation channels’, Telecommunications and Systems Engineering, vol. 1, no. 2, pp. 3-164.
Peral-Rosado, J, Bavaro, M, Lopez-Salcedo, J, Seco-Granados, G, Chawdhry, P, Fortuny-Guasch, J,… Crisci, M 2015, ‘Floor detection with indoor vertical positioning in LTE femtocell networks’, Globecom Workshops, vol. 1, no. 1, pp. 3-16.
Peral-Rosado, J, Lopez-Salcedo, J, Zanier, F & Crisci, M 2012, ‘Achievable localization accuracy of the positioning reference signal of 3GPP LTE’, Localization and GNSS, vol. 2, no. 2, pp. 3-20.
Roth, J, Tummala, M & Scrofani, J 2016, ‘Cellular synchronization assisted refinement (CeSAR): a method for accurate geolocation in LTE-A networks’, System Sciences, vol. 49, no. 1, pp. 3-25.
Thorpe, M 2012, ‘LTE positioning technology for mobile devices: test challenges and solutions’, Spirent, vol. 4, no. 7, pp. 1-20.
Vaghefi, R & Buehrer, R 2014, ‘Improving positioning in LTE through collaboration’, Positioning, Navigation and Communication (PNC), vol. 2, no. 1, pp. 167-190.
Vaghefi, R & Buehrer, R 2015, ‘Cooperative RF pattern matching positioning for LTE cellular systems’, Personal, Indoor, and Mobile Radio Communication (PIMRC), vol. 3, no. 1, pp. 1-6.
Wu, M, Yin, B, Wang, G, Dick, C, Cavallaro, J & Studer, C 2014, ‘Large-scale MIMO detection for 3GPP LTE: algorithms and FPGA implementations’, Signal Processing, vol. 8, no. 5, pp. 916-929.
Xu, E, Ding, Z & Dasgupta, S 2013, ‘Target tracking and mobile sensor navigation in wireless sensor networks’, IEEE Transactions on Mobile Computing, vol. 12, no. 1, pp. 177-186.
Zhang, T, Xiao, D, Cui, J & Luo, X 2012, ‘A novel OTDOA positioning scheme in heterogeneous LTE-advanced systems, Network Infrastructure and Digital Content, vol. 1, no. 2, pp. 135-149.