3 research outputs found
Zero-Forcing Based Downlink Virtual MIMO-NOMA Communications in IoT Networks
To support massive connectivity and boost spectral efficiency for internet of
things (IoT), a downlink scheme combining virtual multiple-input
multiple-output (MIMO) and nonorthogonal multiple access (NOMA) is proposed.
All the single-antenna IoT devices in each cluster cooperate with each other to
establish a virtual MIMO entity, and multiple independent data streams are
requested by each cluster. NOMA is employed to superimpose all the requested
data streams, and each cluster leverages zero-forcing detection to de-multiplex
the input data streams. Only statistical channel state information (CSI) is
available at base station to avoid the waste of the energy and bandwidth on
frequent CSI estimations. The outage probability and goodput of the virtual
MIMO-NOMA system are thoroughly investigated by considering Kronecker model,
which embraces both the transmit and receive correlations. Furthermore, the
asymptotic results facilitate not only the exploration of physical insights but
also the goodput maximization. In particular, the asymptotic outage expressions
provide quantitative impacts of various system parameters and enable the
investigation of diversity-multiplexing tradeoff (DMT). Moreover, power
allocation coefficients and/or transmission rates can be properly chosen to
achieve the maximal goodput. By favor of Karush-Kuhn-Tucker conditions, the
goodput maximization problems can be solved in closed-form, with which the
joint power and rate selection is realized by using alternately iterating
optimization.Besides, the optimization algorithms tend to allocate more power
to clusters under unfavorable channel conditions and support clusters with
higher transmission rate under benign channel conditions
Zero-forcing Oriented Power Minimization for Multi-cell MISO-NOMA Systems: A Joint User Grouping, Beamforming and Power Control Perspective
International audienceFuture wireless communication systems have been imposed high requirement on power efficiency for operator's profitability as well as to alleviate information and communication technology (ICT) global carbon emission. To meet these challenges, the power consumption minimization problem for a generic multi-cell multiple input and single output non-orthogonal multiple access (MISO-NOMA) system is studied in this work. The associated joint user grouping, beamforming (BF) and power control problem is a mixed integer non-convex programming problem, which is tackled by an iterative distributed methodology. Towards this end, the near-optimal zero-forcing (ZF) BF is leveraged, wherein the semiorthogonal user selection (SUS) strategy is applied to select BF users. Based on these, the BF vectors and BF users are determined for each cell using only local information. Then, two distributed user grouping strategies are proposed. The first one, called channel condition based user clustering (CCUC), performs user grouping in each cell based on the channel conditions. This is conducted independently of the power control part and has low computational complexity. Another algorithm, called power consumption based user clustering (PCUC), uses both the channel conditions and inter-cell interference information to minimize each cell's power consumption. In contrary to CCUC, PCUC is optimized jointly with the power control. Finally, with the obtained user grouping and BF vectors, the resultant power allocation problem is optimally solved via an iterative algorithm, whose convergence is mathematically proven given that the problem is feasible. We perform Monte-Carlo simulation and numerical results show that the proposed resource management methods outperform various conventional MISO schemes and the non-clustered MISO-NOMA strategy in several aspects, including power consumption, outage probability, energy efficiency, and connectivity efficiency