2,553 research outputs found
On the Fundamental Limits of Random Non-orthogonal Multiple Access in Cellular Massive IoT
Machine-to-machine (M2M) constitutes the communication paradigm at the basis
of Internet of Things (IoT) vision. M2M solutions allow billions of multi-role
devices to communicate with each other or with the underlying data transport
infrastructure without, or with minimal, human intervention. Current solutions
for wireless transmissions originally designed for human-based applications
thus require a substantial shift to cope with the capacity issues in managing a
huge amount of M2M devices. In this paper, we consider the multiple access
techniques as promising solutions to support a large number of devices in
cellular systems with limited radio resources. We focus on non-orthogonal
multiple access (NOMA) where, with the aim to increase the channel efficiency,
the devices share the same radio resources for their data transmission. This
has been shown to provide optimal throughput from an information theoretic
point of view.We consider a realistic system model and characterise the system
performance in terms of throughput and energy efficiency in a NOMA scenario
with a random packet arrival model, where we also derive the stability
condition for the system to guarantee the performance.Comment: To appear in IEEE JSAC Special Issue on Non-Orthogonal Multiple
Access for 5G System
Interference mitigation using group decoding in multiantenna systems
fi=vertaisarvioitu|en=peerReviewed
Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems
In this work, decision feedback (DF) detection algorithms based on multiple
processing branches for multi-input multi-output (MIMO) spatial multiplexing
systems are proposed. The proposed detector employs multiple cancellation
branches with receive filters that are obtained from a common matrix inverse
and achieves a performance close to the maximum likelihood detector (MLD).
Constrained minimum mean-squared error (MMSE) receive filters designed with
constraints on the shape and magnitude of the feedback filters for the
multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive
implementation of the proposed MB-MMSE-DF detector is developed along with a
recursive least squares-type algorithm for estimating the parameters of the
receive filters when the channel is time-varying. A soft-output version of the
MB-MMSE-DF detector is also proposed as a component of an iterative detection
and decoding receiver structure. A computational complexity analysis shows that
the MB-MMSE-DF detector does not require a significant additional complexity
over the conventional MMSE-DF detector, whereas a diversity analysis discusses
the diversity order achieved by the MB-MMSE-DF detector. Simulation results
show that the MB-MMSE-DF detector achieves a performance superior to existing
suboptimal detectors and close to the MLD, while requiring significantly lower
complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications,
201
Minimum mean-squared error iterative successive parallel arbitrated decision feedback detectors for DS-CDMA systems
In this paper we propose minimum mean squared error (MMSE) iterative successive parallel arbitrated decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems. We describe the MMSE design criterion for DF multiuser detectors along with successive, parallel and iterative interference cancellation structures. A novel efficient DF structure that employs successive cancellation with parallel arbitrated branches and a near-optimal low complexity user ordering algorithm are presented. The proposed DF receiver structure and the ordering algorithm are then combined with iterative cascaded DF stages for mitigating the deleterious effects of error propagation for convolutionally encoded systems with both Viterbi and turbo decoding as well as for uncoded schemes. We mathematically study the relations between the MMSE achieved by the analyzed DF structures, including the novel scheme, with imperfect and perfect feedback. Simulation results for an uplink scenario assess the new iterative DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellation methods against existing ones
Cognitive Wyner Networks with Clustered Decoding
We study an interference network where equally-numbered transmitters and
receivers lie on two parallel lines, each transmitter opposite its intended
receiver. We consider two short-range interference models: the "asymmetric
network," where the signal sent by each transmitter is interfered only by the
signal sent by its left neighbor (if present), and a "symmetric network," where
it is interfered by both its left and its right neighbors. Each transmitter is
cognizant of its own message, the messages of the transmitters to its
left, and the messages of the transmitters to its right. Each receiver
decodes its message based on the signals received at its own antenna, at the
receive antennas to its left, and the receive antennas to its
right. For such networks we provide upper and lower bounds on the multiplexing
gain, i.e., on the high-SNR asymptotic logarithmic growth of the sum-rate
capacity. In some cases our bounds meet, e.g., for the asymmetric network. Our
results exhibit an equivalence between the transmitter side-information
parameters and the receiver side-information parameters in the sense that increasing/decreasing or by a positive
integer has the same effect on the multiplexing gain as
increasing/decreasing or by . Moreover---even in
asymmetric networks---there is an equivalence between the left side-information
parameters and the right side-information parameters .Comment: Second revision submitted to IEEE Transactions on Information Theor
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