2,893 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
Filter Bank Multicarrier for Massive MIMO
This paper introduces filter bank multicarrier (FBMC) as a potential
candidate in the application of massive MIMO communication. It also points out
the advantages of FBMC over OFDM (orthogonal frequency division multiplexing)
in the application of massive MIMO. The absence of cyclic prefix in FBMC
increases the bandwidth efficiency. In addition, FBMC allows carrier
aggregation straightforwardly. Self-equalization, a property of FBMC in massive
MIMO that is introduced in this paper, has the impact of reducing (i)
complexity; (ii) sensitivity to carrier frequency offset (CFO); (iii)
peak-to-average power ratio (PAPR); (iv) system latency; and (v) increasing
bandwidth efficiency. The numerical results that corroborate these claims are
presented.Comment: 7 pages, 6 figure
Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
This article provides an overview of the state-of-art results on
communication resource allocation over space, time, and frequency for emerging
cognitive radio (CR) wireless networks. Focusing on the
interference-power/interference-temperature (IT) constraint approach for CRs to
protect primary radio transmissions, many new and challenging problems
regarding the design of CR systems are formulated, and some of the
corresponding solutions are shown to be obtainable by restructuring some
classic results known for traditional (non-CR) wireless networks. It is
demonstrated that convex optimization plays an essential role in solving these
problems, in a both rigorous and efficient way. Promising research directions
on interference management for CR and other related multiuser communication
systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex
optimization for signal processin
Physical-Layer Security with Multiuser Scheduling in Cognitive Radio Networks
In this paper, we consider a cognitive radio network that consists of one
cognitive base station (CBS) and multiple cognitive users (CUs) in the presence
of multiple eavesdroppers, where CUs transmit their data packets to CBS under a
primary user's quality of service (QoS) constraint while the eavesdroppers
attempt to intercept the cognitive transmissions from CUs to CBS. We
investigate the physical-layer security against eavesdropping attacks in the
cognitive radio network and propose the user scheduling scheme to achieve
multiuser diversity for improving the security level of cognitive transmissions
with a primary QoS constraint. Specifically, a cognitive user (CU) that
satisfies the primary QoS requirement and maximizes the achievable secrecy rate
of cognitive transmissions is scheduled to transmit its data packet. For the
comparison purpose, we also examine the traditional multiuser scheduling and
the artificial noise schemes. We analyze the achievable secrecy rate and
intercept probability of the traditional and proposed multiuser scheduling
schemes as well as the artificial noise scheme in Rayleigh fading environments.
Numerical results show that given a primary QoS constraint, the proposed
multiuser scheduling scheme generally outperforms the traditional multiuser
scheduling and the artificial noise schemes in terms of the achievable secrecy
rate and intercept probability. In addition, we derive the diversity order of
the proposed multiuser scheduling scheme through an asymptotic intercept
probability analysis and prove that the full diversity is obtained by using the
proposed multiuser scheduling.Comment: 12 pages. IEEE Transactions on Communications, 201
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