3,274 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
Subcarrier and Power Allocation for LDS-OFDM System
Low Density Signature-Orthogonal Frequency Division Multiplexing (LDS-OFDM) has been introduced recently as an efficient multiple access technique. In this paper, we focus on the subcarrier and power allocation scheme for uplink LDS-OFDM system. Since the resource allocation problem is not convex due to the discrete nature of subcarrier allocation, the complexity of finding the optimal solutions is extremely high. We propose a heuristic subcarrier and power allocation algorithm to maximize the weighted sum-rate. The simulation results show that the proposed algorithm can significantly increase the spectral efficiency of the system. Furthermore, it is shown that LDS-OFDM system can achieve an outage probability much less than that for OFDMA system
Simplified Multiuser Detection for SCMA with Sum-Product Algorithm
Sparse code multiple access (SCMA) is a novel non-orthogonal multiple access
technique, which fully exploits the shaping gain of multi-dimensional
codewords. However, the lack of simplified multiuser detection algorithm
prevents further implementation due to the inherently high computation
complexity. In this paper, general SCMA detector algorithms based on
Sum-product algorithm are elaborated. Then two improved algorithms are
proposed, which simplify the detection structure and curtail exponent
operations quantitatively in logarithm domain. Furthermore, to analyze these
detection algorithms fairly, we derive theoretical expression of the average
mutual information (AMI) of SCMA (SCMA-AMI), and employ a statistical method to
calculate SCMA-AMI based specific detection algorithm. Simulation results show
that the performance is almost as well as the based message passing algorithm
in terms of both BER and AMI while the complexity is significantly decreased,
compared to the traditional Max-Log approximation method
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