Analysis and Optimization of Massive Access to the IoT Relying on Multi-Pair Two-Way Massive MIMO Relay Systems
Abstract : We investigate massive access in the Internet-ofThings (IoT) relying on multi-pair two-way amplify-and-forward (AF) relay systems using massive multiple-input multiple-output (MIMO). We utilize the approximate message passing (AMP) algorithm for joint device activity detection and channel estimation. Furthermore, we analyze the achievable rates for multiple pairs of active devices and derive the closed-form expressions for both maximum-ratio combining/maximum-ratio transmission (MRC/MRT) and zero-forcing reception/zero-forcing transmission (ZFR/ZFT)-based beamforming schemes adopted at the relay. Moreover, to improve the achievable sum rates, we propose a low-complexity algorithm for optimizing the pilot length L. Our simulation results verify the accuracy of the closed-form expressions of the MRC/MRT and ZFR/ZFT scenarios. Finally, the proposed pilot-length optimization algorithm performs well in both the MRC/MRT and ZFR/ZFT scenarios.
? We compare the GEE of the proposed design with existing FD systems and quantify the improvement achieved by the proposed algorithm.
? These closed-form achievable-rate expressions which are valid for an arbitrary number of relay antennas, are more general than the ones in the existing mMIMO relaying literature.
? We also exhaustively compared the SE and GEE of the proposed FD relaying system to the existing state-of-the-art HD relaying systems, and characterized the values of SI and IUI, for which the proposed system outperforms the existing ones.
? We showed that the proposed algorithms not only outperform existing schemes, but also allow weight adjustment to prioritize user’s energy efficiency requirements.
? Due to the sparse nature of access in the IoT, DAD and CE can be transformed into a compressed sensing problem.
? We prove that these pair of optimization problems can be approximated by convex optimization problems.
? Then, we propose a binary search algorithm for solving these problems, and show that this optimization algorithm has a low complexity.
? We propose the low-complexity procedure of Algorithm 1 to solve these two optimization problems.
? We approximated the non-convex pilot length optimization problems of maximizing the sum rate by tractable convex optimization problems.
• The proposed FD GEE optimization framework can also be used for evaluating GEE of mMIMO HD AF systems which has not been investigated in the open literature.
• We also compare GEE of the proposed FD system to that of its HD counterparts, and characterize the self-loop and inter-user interference regimes, for which the proposed FD system outperforms the HD ones.
• We numerically analyze the effect of weights on the EE of individual users, and show that the proposed framework enable us to meet the heterogeneous EE requirements.
• The proposed FD WSEE framework can also be used to evaluate the WSEE of mMIMO HD system which, to the best of our knowledge, has not been investigated.
? These studies proved that the AMP algorithm has a remarkable capability of balancing its performance by complexity trade-off.
? However, these algorithms do not have a rigorous performance analysis, which is usually required by researchers to study the system performance.
? Energy efficiency (EE) metric, which relies on the Pareto-optimality between throughput and energy consumption, has recently drawn attention as a useful performance measure.
? It is known that DF relay can give better performance than AF relay as it cleans up the noise.
? The SE, which measures how well the spectrum resources are used, is one of the important criteria utilized to define wireless communication performance.
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