An article recently published in the journal Electronic letter demonstrated the feasibility of using a new privacy-preserving blockchain-enabled handover framework in a high-mobility train network.
Study: Blockchain-enabled handover shopping for highly mobile train passengers. Image credit: CHEN MIN CHUN/Shutterstock.com
Background
The increasing demand for data traffic due to the constant use of the mobile network has resulted in the development of small cells (SC). SCs form a dense network that meets the network capacity needs of daily train passengers in a high-mobility train network.
However, frequent and unnecessary handovers in such networks due to short travel times and reduction of cell sizes lead to loss of communication, which can negatively affect the speed of data transfers and the overall quality of service.
In ultra-dense networks, tracking and monitoring the passenger paths to maintain a good quality of service with intelligent handover management, reduced costs and increased throughput is significantly difficult as limited resources are available for fast-moving train passengers.
Passenger movements analyzed using conventional mobility prediction models are used as input in machine learning (ML) to establish the best chosen daily routes. However, these models do not take into account handover delay tolerance and last hop signal strength.
Intelligent handover processes can ensure that passengers remain within service footprints throughout the route to prevent waste of resources. For example, smart handover management can be implemented considering estimated user paths and topology awareness.
In smart handover management, the handover decisions are made based on the cell sizes and cell locations to identify the nearest handover and base station to the users. However, most handover shopping schemes require user data collection, which is becoming increasingly challenging due to the growing privacy awareness among users.
Traditional user tracking applications, such as the Trace Together app and Google Apple Contact Tracing, have several drawbacks, including high risk to users’ privacy, due to heavy reliance on third-party and central servers for alerts and contact matching.
An innovative approach is therefore required to ensure secure and anonymous collection of data from users with their consent. Blockchain decentralized data management frameworks are considered to be promising alternatives since they are less vulnerable to errors, more transparent, anonymous, more secure and do not rely on central servers.
The framework ensures users’ privacy by using pseudonymous addresses and data encryption methods.
Proposed blockchain HO skips architecture, data structure and flow. A specific westbound train line is considered a use case. Image credit: Hussain, S et al., Electronics Letters
The study
In this study, researchers proposed a new blockchain-enabled privacy-preserving handover framework using the train mobility dataset from the City of London. The passenger traffic flows were modeled based on a complex dataset by averaging station footfalls and different train lines using blockchain to ensure privacy. In the framework, pseudonymous addresses were stored to track and monitor the user path.
System model
The proposed framework considered a downlink flow with multiple base stations spread over the London Overground and Underground (LOU) network. A specific westbound train line in a specific rectangular geographical area with L1 and I2 pages around the LOU train network were assessed as the use case.
Base stations were distributed uniformly with λ rate in the rectangular area according to Poisson Point Process (PPP) mobility. Each base station had a specific bandwidth and transmission power. Moreover, the framework was also composed of predefined train speed v and S stations, where users can leave/board the train.
Passenger modeling was based on the distance of the passengers from the base stations around the train network in the framework. All passengers, whether disembarking at stations or in train carriages, were represented as U = 1, 2, . . . , u with base stations as B = 1, 2, . . . , bk for a user association rule.
Reference signal received power (RSRP) measurements were performed by identifying the location of passengers in the train and their connection to the nearest e-NodeB (eNB) base station.
Signal-to-interference to noise ratio (SINR) was used to measure the average RSRP sum of passengers to the average interference sum of noise. Users were assigned the base station with the best SINR based on the SINR measurements.
Handover costs associated with handover hopping through the train route were calculated as the product of train speed, delay tolerance for each handover in seconds, and handover rate per time unit. Researchers also measured the average passenger throughput considering the impact of handover and handover speed.
Simulated scenario shows the set of BSs skipped and connected (one) the hybrid approach, and (b) the proposed approach. Image credit: Hussain, S et al., Electronics Letters
Significance of the study
The new handover delivery framework effectively tracked the individual users through train stations in a high mobility train network using the blockchain methodology. In this framework, the downloaded mobile application in passengers’ smartphones automatically interacted with the stations’ access point when they entered a train station and sent some basic information, including pseudonymous addresses to passengers that hide their identity and their inbound/outbound stations.
Each base station was considered a blockchain node in the framework of information exchange and communication. The collected user information was readily available at all base stations after the blocks were validated by the blockchain, which was then used for individual handover decisions for each passenger.
Calculated blockchain storage and transactions per second required. Image credit: Hussain, S et al., Electronics Letters
Thus, the blockchain provided end-to-end security throughout the passenger lane and was not used at every step of the handover process. A step-by-step handover process was also performed with an additional blockchain security layer.
The proposed handover framework served as a private and secure platform for train passengers while analyzing their future directions and mobility predictions by collecting their data with their consent throughout the journey. In particular, the proposed framework ensured maximum privacy while observing the passenger trajectory considering the passenger’s location and travel paths as well as cell sizes.
User-specific handover hopping was successfully achieved based on individual user information due to the deployment of blockchain framework over existing handover hopping, leading to a better trade-off in terms of last-hop signal quality, user quality of service and network handover. cost. The framework increased average throughput by 2% and last hop signal quality by 100% and reduced network handover costs by 50%.
References
Hussain, S., Asad, S.M., Imran, M.A., et al. (2022) Blockchain-Enabled Handover Shopping for High Mobility Train Passengers. Electronic letter. https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/ell2.12658
