We present a Machine Learning (ML) use-case for reducing latency in wireless networks, by replacing some of the traditional and time-consuming procedures. The proposed method reduces the time needed for collecting a large number of measurements for the target cell selection during the inter-frequency handover procedure. Our paper contributes to the current literature, firstly, by showcasing how ML can replace traditional procedures in order to reduce the latency. Secondly, by presenting results based on the real measurements from a live network. Finally, by training a huge number of models over a large geographical area, where multiple base stations are deployed, reporting the performance over all those models. This contribution extends previous work in the area, that was based on simulations and improves confidence in the applicability of the proposed solution in real networks. The proposed method not only reduces the total handover delay and service disruption but can also be considered as an enabler for new verticals and use-cases, as we discuss in this paper.

Seamless wireless connectivity and low latency communication in mobility scenarios are two fundamental requirements in the fifth generation networks to effectively cover a broader range of use cases such as massive machine type communications and ultra-reliable low-latency communications for new industrial/potential users, as well as enhanced mobile broadband for conventional users. In this paper, we aim at measuring certain key performance indicators in mobility scenarios, highlighting some practical inefficiencies that require more careful consideration when designing and enhancing mobility features of 5G networks. We investigate the round trip time, uplink throughput and the impact of handover interruption time on these metrics. Our results are based on three months experiment campaign in a mix of rural, suburban, and urban environment using the geographically distributed MONROE platform. Based on the observed discrepancies between measured and standardized LTE performance, we conclude the paper with a discussion of techniques that may need more attention for mobility scenarios in fifth generation mobile networks.

One of the first key self-organizing features introduced in LTE was Automatic Neighbor Relations (ANR), a function for automatically generating relations between radio network entities that is needed for many features such as active-mode mobility, load balancing and dual connectivity. Given the benefits of ANR in LTE, we foresee that procedures for relations establishment will be an important integrated part of 5G systems as well. Moreover, the new emerging technology components of 5G such as massive beamforming expand the scope of relations beyond the neighbor relations of LTE. In this paper, we give an overview of key 5G radio access components, discuss the need for different types of identifiers and relations, and comment on the impact from the ultra-lean design principle of 5G. The paper also discusses some possible procedures for automatic relation establishment in consideration of the specific 5G aspects.

We present a fast algorithm that, for a given input sequence and a linear channel code, computes the syndrome posterior probability (SPP) of the code, i.e., the probability that all parity check relations of the code are satisfied. According to this algorithm, the SPP can be computed blindly, i.e., given the soft information on a received sequence we can compute the SPP for the code without first decoding the bits. We show that the proposed scheme is efficient by investigating its computational complexity. We then consider two scenarios where our proposed SPP algorithm can be used. The first scenario is when we are interested in finding out whether a certain code was used to encode a data stream. We formulate a statistical hypothesis test and we investigate its performance. We also compare the performance of our scheme with that of an existing scheme. The second scenario deals with how we can use the algorithm for reducing the computational complexity of a blind decoding process. We propose a heuristic sequential statistical hypotheses test to use the fact that in real applications, the data arrives sequentially, and we investigate its performance using system simulations.

We present a scheme for reducing the part of the downlink signaling traffic in wireless multiple access systems that contains scheduling information. The theoretical basis of the scheme is that the scheduling decisions made by the base station are correlated with the CSI reports from the mobiles. This correlation can be exploited by the source coding scheme that is used to compress the scheduling maps before they are sent to the mobiles. In the proposed scheme, this idea is implemented by letting the mobiles make tentative scheduling decisions themselves, and then letting the base station transmit "agreement maps" instead of raw scheduling maps to the mobiles. The agreement maps have lower entropy and they require less resources to be transmitted than the original scheduling maps do. The improvement can be substantial. We also model the task of finding the optimal scheduling assignments according to the proposed scheme as a combinatorial optimization problem and present an efficient algorithm to find the optimal solution.

Blind decoding, used on control channels of some multi-user wireless access systems, is a technique for achieving adaptive modulation and coding. The idea is to adapt the modulation and coding scheme to the channel quality but instead of signaling the parameters used explicitly, the receiver blindly tries a number of fixed parameter combinations until a successful decoding attempt is detected, with the help of a cyclic redundancy check. In this paper we suggest a new method for reducing the complexity and energy consumption associated with such blind decoding schemes. Our idea is to use a mini-CRC injected early in the data stream to determine if the current decoding attempt is using the correct modulation and coding parameters. We analyze and exemplify the complexity gain of this approach and also investigate the impact of the rearrangement of the CRC scheme in terms of the probability of undetected error. The presented results for the complexity gain are promising and the impact on the error detection capability turns out to be small if any.

We present a fast mechanism for determining which channel code that was used on a communication link. In the proposed scheme, the receiver does not need to receive the entire data to determine the actual code. Moreover, the proposed scheme can also be used to determine the interleaving/scrambling sequence that was used at the transmitter. We investigate the performance of the scheme for some standard convolutional codes.

This paper considers the control signaling on the downlink in wireless multiple access systems, with focus on the part of the control signaling that carries information on the user's time/frequency scheduling assignments. A new idea is presented to reduce the amount of channel resources needed for this signaling. The idea is to exploit the fact that provided that only one single user is scheduled on each channel resource, then the different users' scheduling assignments are correlated. This correlation can be exploited by encoding the scheduling information differentially. In order to recover the scheduling information, a user must then decode the scheduling information of some of the others. This is possible, because on the downlink, all users can hear the transmission by the base station so that users with a high SNR may decode the control signaling sent to users with a lower SNR. We present a practical scheme to exploit this idea. Both analytical analysis and numerical examples illustrate that the proposed technique can provide a substantial reduction in signaling traffic.

We present an idea to reduce the part of the downlink signaling traffic in wireless multiple access systems that contains scheduling information. The theoretical basis of the scheme is that the scheduling decisions made by the base station are correlated with the CSI reports from the mobiles. This correlation can be exploited by the source coding scheme that is used to compress the scheduling maps before they are sent to the mobiles. In the proposed scheme, this idea is implemented by letting the mobiles make tentative scheduling decisions themselves, and then letting the base station transmit "agreement maps" instead of raw scheduling maps to the mobiles. The agreement maps have lower entropy and they require less resources to be transmitted than the original scheduling maps do. The improvement can be substantial.

Control signaling strategies for scheduling information in cellular OFDM systems are studied. A single-cell multiuser system model is formulated that provides system capacity estimates accounting for the signaling overhead. Different scheduling granularities are considered, including the one used in the specifications for the 3G Long Term Evolution (LTE). A greedy scheduling method is assumed, where each resource is assigned to the user for which it can support the highest number of bits. The simulation results indicate that the cost of control signaling does not outweigh the scheduling gain, when compared with a simple round-robin scheme that does not need signaling of scheduling information. Furthermore, in the studied scenario, joint coding and signaling of scheduling information over all selected users is found to be superior to separate coding and signaling for each user. The results also indicate that the scheduling granularity used for LTE provides better performance than the full granularity.