PROJECT TITLE :

Massive Connectivity With Massive MIMO—Part I: Device Activity Detection and Channel Estimation - 2018

ABSTRACT:

This 2-half paper considers an uplink large device communication scenario in which a large number of devices are connected to a base station (BS), however user traffic is sporadic therefore that in any given coherence interval, solely a subset of users is active. The target is to quantify the value of active user detection and channel estimation and to characterize the achievable rate of a grant-free two-phase access theme in which device activity detection and channel estimation are performed jointly using pilot sequences in the first part and data is transmitted within the second phase. So as to accommodate a large range of simultaneously transmitting devices, this Project studies an asymptotic regime where the BS is supplied with a massive number of antennas. The most contributions of Half I of this Project are as follows. Initial, we have a tendency to note that as a consequence of having a large pool of probably active devices however restricted coherence time, the pilot sequences cannot all be orthogonal. But, despite the nonorthogonality, this Project shows that in the asymptotic huge multiple-input multiple-output regime, both the missed device detection and therefore the false alarm possibilities for activity detection can continually be created to go to zero by utilizing compressed sensing techniques that exploit sparsity within the user activity pattern. Half II of this Project more characterizes the achievable rates using the proposed theme and quantifies the price of using nonorthogonal pilot sequences for channel estimation in achievable rates.


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