Adaptive modulation systems for predicted wireless channels

This paper addresses robust link adaptation for a precoded downlink multiple input single output (MISO) system, for guaranteeing ultra-reliable (99.999%) transmissions to mobile users served by a small cell network (e.g. slowly moving machines in a factory). Effects of inaccurate channel state information (CSI) caused by user mobility and varying precoders in neighboring cells are mitigated. Both of these impairments translate to changes of received signal-to-noise plus interference ratios (SINRs), leading to CSI mispredictions and potentially erroneous transmissions. Knowing the statistics of the propagation channels and the precoder variation, backoff values can be selected to guarantee robust link adaptation. Combining this with information on the current channel state, transmissions can be adapted to have a desired reliability. Theoretical analysis accompanied by simulation results show that the proposed approach is suitable for attaining 5G ultra-reliability targets in realistic settings.

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“…These two channels are correlated for short delays τ. The effect of channel dispersion due to Doppler shift can be modeled by [20] …”

Section: Sinr Realized At Time Of Transmissionmentioning

confidence: 99%

Ultra-Reliable Link Adaptation for Downlink MISO Transmission in 5G Cellular Networks

2016

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“…An effective method to improve the spectral efficiency in a wireless communication system is the use of adaptive modulation and coding (AMC) [1,2]. A higher order modulation provides a better spectral efficiency at the expense of a worse error rate performance; a lower rate channel coding generally provides a better error rate performance at the cost of a poorer spectral efficiency.…”

Section: Introductionmentioning

confidence: 99%

A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA

Aydın¹,

Kwan²,

Leung³

et al. 2013

Applied Soft Computing

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Abstract. Multiuser scheduling is an important aspect in the performance optimization of a wireless network since it allows multiple users to access a shared channel efficiently by exploiting multiuser diversity. To perform efficient scheduling, channel state information (CSI) for users is required, and is obtained via their respective feedback channels. In this paper, a more realistic imperfect CSI feedback, in the form of a finite set of Channel Quality Indicator (CQI) values, is assumed as specified in the HSDPA standard. A mathematical model of the problem is developed for use in the optimization process. A hybrid heuristic approach based on particle swarm optimization and simulated annealing is used to solve the problem. Simulation results indicate that the hybrid approach outperforms individual implementations of both simulated annealing and particle swarm optimisation.

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“…The rate performance of BE connections is also evaluated by average service rate ˆηi(t) over a window size tc = 1000 ms based on (8). The system is simulated over 60000 ms with bounds βrtPS = 1.0, βnrtPS = 0.8, and βBE = 0.6.…”

Section: Parameter Settingmentioning

confidence: 99%

QoS Support for Cross-Layer Scheduling Algorithm in Wireless Networks

2016

IJSR

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Scheduling plays an crucial role in providing quality of service (QoS) support to multimedia communications in different kinds of wireless networks, including wireless sensor networks, cellular networks and mobile ad hoc networks. The authors proposed a scheduling algorithm at the medium access control (MAC) layer for multiple connections with diverse QoS requirements, where every connection employs adaptive modulation and coding (AMC) scheme at the physical (PHY) layer over wireless fading channels. Each connection is assigned with a priority, which is updated dynamically based upon its channel and service status; the connection with highest priority is scheduled every time. The authors scheduler provides diverse QoS guarantees, uses wireless bandwidth efficiently, and enjoys scalability, flexibility and low implementation complexity. Its performance cab be evaluated via simulations.

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Adaptive modulation systems for predicted wireless channels

Cited by 46 publications

References 22 publications

Ultra-Reliable Link Adaptation for Downlink MISO Transmission in 5G Cellular Networks

Ultra-Reliable Link Adaptation for Downlink MISO Transmission in 5G Cellular Networks

A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA

QoS Support for Cross-Layer Scheduling Algorithm in Wireless Networks

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