Cellular networks continue to trend rapidly towards more bands and carrier frequencies, along with higher base station density, requiring complex decisions to be made when associating a mobile user with a band and cell. This paper develops a novel approach to optimizing frequency band and cell selection while taking into account user mobility and handovers. This is a complex problem because of the uncertain link failure events, handover related overheads, and the significant difference in the propagation characteristics between different frequency bands. The network dynamics due to user mobility are modeled as a Markov decision process, and we develop a recurrent Q-learning framework to exploit the relationship between user trajectories and the history of SINR measurements. The effective cell boundaries are therefore based on user trajectories and velocities rather than just position and signal strength. Detailed system-level simulations show that the proposed learning-based approach improves the throughput of the edge users by 54% and the median throughput by 34% compared to traditional SINR-based association and achieves a superior rate/coverage tradeoff (quantified as sum-log-rate) compared to SINR or signal-strength-based associations.

Wireless cellular networks have many parameters that are normally tuned upon deployment and re-tuned as the network changes. Many operational parameters affect reference signal received power (RSRP), reference signal received quality (RSRQ), signal-to-interference-plus-noise-ratio (SINR), and, ultimately, throughput. In this paper, we develop and compare two approaches for maximizing coverage and minimizing interference by jointly optimizing the transmit power and downtilt (elevation tilt) settings across sectors. To evaluate different parameter configurations offline, we construct a realistic simulation model that captures geographic correlations. Using this model, we evaluate two optimization methods: deep deterministic policy gradient (DDPG), a reinforcement learning (RL) algorithm, and multi-objective Bayesian optimization (BO). Our simulations show that both approaches significantly outperform random search and converge to comparable Pareto frontiers, but that BO converges with two orders of magnitude fewer evaluations than DDPG. Our results suggest that data-driven techniques can effectively self-optimize coverage and capacity in cellular networks.

An effective method for mitigating transmitter nonlinear echo in 10GBASE-T transceivers is discussed. This method is based on approximating the nonlinear characteristics of the combined transmitter and the echo channel by smooth multidimensional functions. Results based on a chip fabricated in 0.13 mum CMOS technology show that approximately 6 dB of average cancellation of nonlinear echo can be achieved by this method.

The mobile communication industry in the United States is undergoing major changes. Auctioning of additional spectrum will lead to more service providers and will significantly increase competition. Service providers are likely to customize the services they offer to differentiate themselves from others. We discuss possible technologies for differentiation of services and the implications of these on the requirements for embedded digital signal processors (DSPs). In the US, supporting at least three widely used air interfaces will be a challenge to the industry. The need for customization in the context of multiple standards will create strong pressure to significantly improve the firmware development environment for DSPs. This also implies evolution to architectures that are more friendly to developers.

A discrete approach to multiple tone modulation is developed for digital communication channels with arbitrary intersymbol interference (ISI) and additive Gaussian noise. Multiple tone modulation is achieved through the concatenation of a finite block length modulator based on discrete Fourier transform (DFT) code vectors, and high gain coset or trellis codes. Symbol blocks from an inverse DFT (IDFT) are cyclically extended to generate ISI-free channel-output symbols that decompose the channel into a group of orthogonal and independent parallel subchannels. Asymptotic performance of this system is derived, and examples of asymptotic and finite block length coding gain performance for several channels are evaluated at different values of bits per sample. This discrete multiple tone technique is linear in both the modulation and the demodulation, and is free from the effects of error propagation that often afflict systems employing bandwidth-optimized decision feedback plus coset codes.>

The authors present techniques for breaking the bottleneck caused by delays in the feedback loop, which can severely limit the maximum data rate of a detector, operating with nonlinear cancellation (NLC). The authors first show how to simplify the loop to avoid high-speed switching of analog signals by using multiple decision elements, each with a different threshold level. The authors then show how to use lookahead computation to increase the delay permissible in the feedback loop. The authors describe nonlinear cancellation, and outline some of the problems of implementing NLC at high data rates. Techniques for overcoming these problems are developed and are illustrated with the example of a simple one-tap NLC. The authors describe how to generalize the techniques to more complex NLCs and present some more examples.>

A linear technique for combining equalization and coset codes on partial response channels with additive white Gaussian noise is developed. The technique, vector coding, uses a set of transmit filters or 'vectors' to partition the channel into an independent set of parallel intersymbol interference (ISI)-free channels for any given finite (or infinite) block length. The optimal transmit vectors for such channel partitioning are shown to be the eigenvectors of the channel covariance matrix for the specified block length, and the gains of the individual channels are the eigenvalues. An optimal bit allocation and energy distribution, are derived for the set of parallel channels, under an accurate extension of the continuous approximation for power in optimal multidimensional signal sets for constellations with unequal signal spacing in different dimensions. Examples are presented that demonstrate performance advantages with respect to zero-forcing decision feedback methods that use the same coset code on the same partial response channel. Only resampling the channel at an optimal rate and assuming no errors in the feedback path will bring the performance of the decision feedback methods up to the level of the vector coded system.>