Implementation of interference cancellation techniques within a dynamic functional split adaptation
Increased interference is one of the main drawbacks of cell densification, which is an important strategy for 5G networks to achieve higher data rates. Function centralization has been proposed as a strategy to counter this problem, by letting the physical or scheduling functions coordinate among one another. The more functions are coordinated, the better their mutual interference can be avoided. Several techniques exist in this regard, ranging from coordinated scheduling to joint transmission and reception. However, experiments showing the effectiveness of implemented interference mitigation techniques under a dynamic functional split adaptation are still missing in the literature. In this thesis, the student will implement, evaluate, and optimize different strategies for mitigating interference in a mobile testbed that changes its functional split at runtime. The student will be provided with a minimally working testbed, which she/he will improve and implement the interference-mitigating techniques on.
Increased interference is one of the main drawbacks of cell densification, which is an important strategy for 5G networks to achieve higher data rates. Function centralization has been proposed as a strategy to counter this problem, by letting the physical or scheduling functions coordinate among one another. Nevertheless, the capacity of the fronthaul network limits the feasibility of this strategy, as the throughput required to connect low level functions is very high. Fortunately, since not every function benefits in the same way from centralization, a more flexible approach can be used. Instead of centralizing all functions, only those providing the highest amount of interference mitigation can be centralized. In addition, the centralization level, or functional split, can be change during runtime according to the instantaneous network conditions. Nonetheless, it is not fully know how costly it is to deploy and operate a network implementing a dynamic functional split.
In this internship, the cost of a radio access network implementing a dynamic functional split will be evaluated. A simulator already developed at LKN will be used and extended to produce network configurations adapted to the instantaneous user position and activity. Then, off-the-shelf cost models will be improved and used to estimate the deployment and operating cost of the network under multiple scenarios. Furthermore, the conditions on which a dynamic functional split is profitable will be investigated. Improvements on the functional-split selection algorithm will be proposed, such that the operator benefits from enhanced performance without operating at exceedingly costly states. Finally, a model that takes into account the cost of finding and implementing a new functional split will be employed and its results compared to the previous results.
Probability parameters of 5G RANs featuring dynamic functional split
The architecture of 5G radio access networks features the division of the base station (gNodeB) into a centralized unit (CU) and a distributed unit (DU). This division enables cost reduction and better user experience via enhanced interference mitigation. Recent research proposes the posibility to modify this functional split dynamically, that is, to lively change the functions that run on the CU and DU. This has interesting implications at the network operation.
In this topic, the student will employ a dedicated simulator developed by LKN to characterize the duration and transition rates of each functional split under multiple variables: population density, mitigation capabilities, mobility, etc. This characterization may be used then on traffic models to predict the network behavior.
MATLAB, some experience with mobile networks and simulators