622 research outputs found
Random Access in Massive MIMO by Exploiting Timing Offsets and Excess Antennas
Massive MIMO systems, where base stations are equipped with hundreds of
antennas, are an attractive way to handle the rapid growth of data traffic. As
the number of user equipments (UEs) increases, the initial access and handover
in contemporary networks will be flooded by user collisions. In this paper, a
random access protocol is proposed that resolves collisions and performs timing
estimation by simply utilizing the large number of antennas envisioned in
Massive MIMO networks. UEs entering the network perform spreading in both time
and frequency domains, and their timing offsets are estimated at the base
station in closed-form using a subspace decomposition approach. This
information is used to compute channel estimates that are subsequently employed
by the base station to communicate with the detected UEs. The favorable
propagation conditions of Massive MIMO suppress interference among UEs whereas
the inherent timing misalignments improve the detection capabilities of the
protocol. Numerical results are used to validate the performance of the
proposed procedure in cellular networks under uncorrelated and correlated
fading channels. With UEs that may simultaneously become active
with probability 1\% and a total of frequency-time codes (in a given
random access block), it turns out that, with antennas, the proposed
procedure successfully detects a given UE with probability 75\% while providing
reliable timing estimates.Comment: 30 pages, 6 figures, 1 table, submitted to Transactions on
Communication
A Belief Propagation Based Framework for Soft Multiple-Symbol Differential Detection
Soft noncoherent detection, which relies on calculating the \textit{a
posteriori} probabilities (APPs) of the bits transmitted with no channel
estimation, is imperative for achieving excellent detection performance in
high-dimensional wireless communications. In this paper, a high-performance
belief propagation (BP)-based soft multiple-symbol differential detection
(MSDD) framework, dubbed BP-MSDD, is proposed with its illustrative application
in differential space-time block-code (DSTBC)-aided ultra-wideband impulse
radio (UWB-IR) systems. Firstly, we revisit the signal sampling with the aid of
a trellis structure and decompose the trellis into multiple subtrellises.
Furthermore, we derive an APP calculation algorithm, in which the
forward-and-backward message passing mechanism of BP operates on the
subtrellises. The proposed BP-MSDD is capable of significantly outperforming
the conventional hard-decision MSDDs. However, the computational complexity of
the BP-MSDD increases exponentially with the number of MSDD trellis states. To
circumvent this excessive complexity for practical implementations, we
reformulate the BP-MSDD, and additionally propose a Viterbi algorithm
(VA)-based hard-decision MSDD (VA-HMSDD) and a VA-based soft-decision MSDD
(VA-SMSDD). Moreover, both the proposed BP-MSDD and VA-SMSDD can be exploited
in conjunction with soft channel decoding to obtain powerful iterative
detection and decoding based receivers. Simulation results demonstrate the
effectiveness of the proposed algorithms in DSTBC-aided UWB-IR systems.Comment: 14 pages, 12 figures, 3 tables, accepted to appear on IEEE
Transactions on Wireless Communications, Aug. 201
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