5,865 research outputs found
Multiuser MIMO-OFDM for Next-Generation Wireless Systems
This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base stationβs or radio portβs coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems
Power Allocation for Adaptive OFDM Index Modulation in Cooperative Networks
In this paper, we propose a power allocation strategy for the adaptive
orthogonal frequency-division multiplexing (OFDM) index modulation (IM) in
cooperative networks. The allocation strategy is based on the
Karush-Kuhn-Tucker (KKT) conditions, and aims at maximizing the average network
capacity according to the instantaneous channel state information (CSI). As the
transmit power at source and relay is constrained separately, we can thus
formulate an optimization problem by allocating power to active subcarriers.
Compared to the conventional uniform power allocation strategy, the proposed
dynamic strategy can lead to a higher average network capacity, especially in
the low signal-to-noise ratio (SNR) region. The analysis is also verified by
numerical results produced by Monte Carlo simulations. By applying the proposed
power allocation strategy, the efficiency of adaptive OFDM IM can be enhanced
in practice, which paves the way for its implementation in the future,
especially for cell-edge communications
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