68 research outputs found
Capacity-Achieving Iterative LMMSE Detection for MIMO-NOMA Systems
This paper considers a iterative Linear Minimum Mean Square Error (LMMSE)
detection for the uplink Multiuser Multiple-Input and Multiple-Output (MU-MIMO)
systems with Non-Orthogonal Multiple Access (NOMA). The iterative LMMSE
detection greatly reduces the system computational complexity by departing the
overall processing into many low-complexity distributed calculations. However,
it is generally considered to be sub-optimal and achieves relatively poor
performance. In this paper, we firstly present the matching conditions and area
theorems for the iterative detection of the MIMO-NOMA systems. Based on the
proposed matching conditions and area theorems, the achievable rate region of
the iterative LMMSE detection is analysed. We prove that by properly design the
iterative LMMSE detection, it can achieve (i) the optimal sum capacity of
MU-MIMO systems, (ii) all the maximal extreme points in the capacity region of
MU-MIMO system, and (iii) the whole capacity region of two-user MIMO systems.Comment: 6pages, 5 figures, accepted by IEEE ICC 2016, 23-27 May 2016, Kuala
Lumpur, Malaysi
Gaussian Message Passing for Overloaded Massive MIMO-NOMA
This paper considers a low-complexity Gaussian Message Passing (GMP) scheme
for a coded massive Multiple-Input Multiple-Output (MIMO) systems with
Non-Orthogonal Multiple Access (massive MIMO-NOMA), in which a base station
with antennas serves sources simultaneously in the same frequency.
Both and are large numbers, and we consider the overloaded cases
with . The GMP for MIMO-NOMA is a message passing algorithm operating
on a fully-connected loopy factor graph, which is well understood to fail to
converge due to the correlation problem. In this paper, we utilize the
large-scale property of the system to simplify the convergence analysis of the
GMP under the overloaded condition. First, we prove that the \emph{variances}
of the GMP definitely converge to the mean square error (MSE) of Linear Minimum
Mean Square Error (LMMSE) multi-user detection. Secondly, the \emph{means} of
the traditional GMP will fail to converge when . Therefore, we propose and derive a new
convergent GMP called scale-and-add GMP (SA-GMP), which always converges to the
LMMSE multi-user detection performance for any , and show that it
has a faster convergence speed than the traditional GMP with the same
complexity. Finally, numerical results are provided to verify the validity and
accuracy of the theoretical results presented.Comment: Accepted by IEEE TWC, 16 pages, 11 figure
Capacity-Achieving MIMO-NOMA: Iterative LMMSE Detection
This paper considers a low-complexity iterative Linear Minimum Mean Square
Error (LMMSE) multi-user detector for the Multiple-Input and Multiple-Output
system with Non-Orthogonal Multiple Access (MIMO-NOMA), where multiple
single-antenna users simultaneously communicate with a multiple-antenna base
station (BS). While LMMSE being a linear detector has a low complexity, it has
suboptimal performance in multi-user detection scenario due to the mismatch
between LMMSE detection and multi-user decoding. Therefore, in this paper, we
provide the matching conditions between the detector and decoders for
MIMO-NOMA, which are then used to derive the achievable rate of the iterative
detection. We prove that a matched iterative LMMSE detector can achieve (i) the
optimal capacity of symmetric MIMO-NOMA with any number of users, (ii) the
optimal sum capacity of asymmetric MIMO-NOMA with any number of users, (iii)
all the maximal extreme points in the capacity region of asymmetric MIMO-NOMA
with any number of users, (iv) all points in the capacity region of two-user
and three-user asymmetric MIMO-NOMA systems. In addition, a kind of practical
low-complexity error-correcting multiuser code, called irregular
repeat-accumulate code, is designed to match the LMMSE detector. Numerical
results shows that the bit error rate performance of the proposed iterative
LMMSE detection outperforms the state-of-art methods and is within 0.8dB from
the associated capacity limit.Comment: Accepted by IEEE TSP, 16 pages, 9 figures. This is the first work
that proves the low-complexity iterative receiver (Parallel Interference
Cancellation) can achieve the capacity of multi-user MIMO systems. arXiv
admin note: text overlap with arXiv:1604.0831
Network-coded MIMO-NOMA systems with FEC codes in two-way relay networks
This paper assumes two users and a two‐way relay network with the combination of 2×2 multi‐input multi‐output (MIMO) and nonorthogonal multiple access (NOMA). To achieve network reliability without sacrificing network throughput, network‐coded MIMO‐NOMA schemes with convolutional, Reed‐Solomon (RS), and turbo codes are applied. Messages from two users at the relay node are network‐coded and combined in NOMA scheme. Interleaved differential encoding with redundancy (R‐RIDE) scheme is proposed together with MIMO‐NOMA system. Quadrature phase‐shift keying (QPSK) modulation technique is used. Bit error rate (BER) versus signal‐to‐noise ratio (SNR) (dB) and average mutual information (AMI) (bps/Hz) versus SNR (dB) in NOMA and MIMO‐NOMA schemes are evaluated and presented. From the simulated results, the combination of MIMO‐NOMA system with the proposed R‐RIDE‐Turbo network‐coded scheme in two‐way relay networks has better BER and higher AMI performance than conventional coded NOMA system. Furthermore, R‐RIDE‐Turbo scheme in MIMO‐NOMA system outperforms the other coded schemes in both MIMO‐NOMA and NOMA systems
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