Efficient Beam Alignment in Millimeter Wave Systems Using Contextual Bandits

In this paper, we investigate the problem of beam alignment in millimeter wave (mmWave) systems, and design an optimal algorithm to reduce the overhead. Specifically, due to directional communications, the transmitter and receiver beams need to be aligned, which incurs high delay overhead since without a priori knowledge of the transmitter/receiver location, the search space spans the entire angular domain. This is further exacerbated under dynamic conditions (e.g., moving vehicles) where the access to the base station (access point) is highly dynamic with intermittent on-off periods, requiring more frequent beam alignment and signal training. To mitigate this issue, we consider an online stochastic optimization formulation where the goal is to maximize the directivity gain (i.e., received energy) of the beam alignment policy within a time period. We exploit the inherent correlation and unimodality properties of the model, and demonstrate that contextual information improves the performance. To this end, we propose an equivalent structured Multi-Armed Bandit model to optimally exploit the exploration-exploitation tradeoff. In contrast to the classical MAB models, the contextual information makes the lower bound on regret (i.e., performance loss compared with an oracle policy) independent of the number of beams. This is a crucial property since the number of all combinations of beam patterns can be large in transceiver antenna arrays, especially in massive MIMO systems. We further provide an asymptotically optimal beam alignment algorithm, and investigate its performance via simulations.Comment: To Appear in IEEE INFOCOM 2018. arXiv admin note: text overlap with arXiv:1611.05724 by other author

THROUGHPUT OPTIMIZATION AND ENERGY ENHANCEMENT IN MASSIVE MIMO SYSTEMS

For the last few decades mobile technologies have undergone enormous transformation. Mobile broadband for cellular networks has been exponentially evolving with time and in order to meet the future expectation for this high demand newer and better technologies have to be invented. The enormous success of smart electronics such as tablets, smart phones and other hand held devices that use the Internet have generated a lot of Internet traffic therefore, diving LTE to its limit. LTE (4G) which is a high speed wireless communication standard for mobile phones and data terminals is a significant upgrade of GSM and UMTS network technologies. The Technology has downlink peak rates of 300Mbits/s and Uplink peak rates of 75Mbits/s with transfer latency rate of less than 5ms. Power Consumption level for LTE is of significant concern as well as the energy consumption in cellular networks. To solve the limitations in LTE, one great candidate is 5G radio standard. 5G relies heavily on massive MIMO to achieve its targets. This thesis looked into significance of Multi-antenna (Massive MIMO) at the BS as a solution for energy efficiency, increased data rates and the reduction of latency rates in wireless broadband communication. And the simulation results proved that Massive MIMO has better performance compared to conventional MIMO.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Influence of human body on massive MIMO indoor channels

© 2019 IEEE. Massive MIMO can dramatically improve capacity and spectral efficiency. However, it is not very clear whether it can significantly improve the signal blockage problem that exists in single antenna systems. In this paper, we investigate the impact of the human body on indoor massive MIMO channels, using practically measured channel data for a 32x8 massive MIMO system in a complex office environment. We introduce a parameter of Power Imbalance (PI) indices to estimate the wide-sense none-stationarity in multiple domains and another parameter of Channel Popularity Indices (CPI) to predict the popularity of MIMO channel. We find that in most cases, the presence of the human body still has a non- negligible negative impact. It decreases the ergodic capacity by about 8% and increases the path loss exponent by 1. In average, the ergodic capacity for NLOS channels are 15% higher than that for LOS