Green Relay Techniques in Cellular Systems

Qi, Yihong; Héliot, Fabien; Imran, Muhammad Ali; Tafazolli, Rahim

doi:10.1201/b13084-4

Cited by 6 publications

(12 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figures and matches up the sum‐rate and EE performances of presented EE‐EBO technique, in contradiction of other previous precoding techniques, which are devoted to reduce the MSE or increase the SE of cooperative MIMO‐AF systems, for n = 4,

P_{S c_{N}}^{\max}

= 80 W,

P_{{italicRe}_{N}}^{\max}

= = 10 W,

σ_{0}^{2}

σ_{1}^{2}

σ_{2}^{2} false/ 10

. Observe that the unit for sum‐rate is bit/2/s, as take the amount of transmitted bits over two transmission phases.…”

Section: Resultsmentioning

confidence: 71%

“…As well, they depend upon the power model parameters of Table in the work of Héliot et al (on the other hand, with

P_{S c_{N}}^{SlA}

= 0 W) for setting values to all the parameters. Furthermore, observe that Po max for each antenna is amid 6 to 20 W for a distinctive micro/macro BS, and among 1 to 5 W for a distinctive urban/rural RN . As well, take a single‐tap i.i.d MIMO Rayleigh fading channel among each node, a unit bandwidth (b = 1).…”

Section: Resultsmentioning

confidence: 99%

“…Observe that the unit for sum‐rate is bit/2/s, as take the amount of transmitted bits over two transmission phases. Since it is anticipated, the precoding techniques in the works of Héliot and Qi et al offer and the presented EE‐ EBO technique offers the finest MSE and sum‐rate performances, correspondingly, while EE‐ EBO technique as well offers the finest energy consumption. Certainly, EE‐ EBO technique could decrease Energy consumption en b in better channel condition

((), while σ_{0}^{2} = - 30 normaldB)

, while matched up with other MSE, increase the SE and EE‐optimal approaches.…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, observe that Po max for each antenna is amid 6 to 20 W for a distinctive micro/macro BS, 5 and among 1 to 5 W for a distinctive urban/rural RN. 28 As well, take a single-tap i.i.d MIMO Rayleigh fading channel among each node, a unit bandwidth (b = 1). Furthermore, we presume that the entire channel matrices contain the identical dimension, that is to say, n = nSc N = nRe N = nDe N and N = 10 in step 1.…”

Section: Resultsmentioning

confidence: 99%

“…In transmission mode, a node takes power for preparing (for example, baseband processing and RF transceiver chain) and forwarding the information (power amplifier). In keeping with the work of Qi et al, the power consumption of general communication equipments/devices in a cooperative MIMO‐AF system, for instance, BS, RN, or user equipment (UE), is linearly rely on their transmit power while transmitting. Therefore, it is stated by means of a generic linear MIMO power model

P o^{Tx} = normalΔ italicPo + n P o^{CipA} + {Po}^{Ci} .

…”

Section: Proposed Methodologymentioning

confidence: 91%

See 4 more Smart Citations

A novel enhanced bat optimization based energy efficiency and imperfect channel state information in cooperative MIMO‐AF systems

Kanithan¹,

Tamilselvan²

2018

Concurrency and Computation

View full text Add to dashboard Cite

Summary Energy Efficiency (EE) is a vital design standard for the future generation of communication systems. Similarly, cooperative communication is extremely efficient for improving the performance of such systems. Current research presents a relay precoding optimization algorithm in order to resolve EE problem in the Multiple‐Input‐Multiple‐Output (MIMO) Amplify‐And‐Forward (AF) Relay Networks containing correct Channel State Information (CSI) only. With the intension of focus on imperfect, this work presents a novel design of MIMO AF Relay Networks under Imperfect CSI (ICSI) by taking Channel Estimation (CE) errors and feedback delay errors, deprived of taking the straight link from source to destination. For this reason, we present a Hidden Semi Markov Model (HSMM) under ICSI, in which the source and destination based relay links are identified through destination. After that, we implement an Enhanced Bat Optimization (EBO) algorithm to enhance the EE of MIMO relay‐based non‐regenerative cooperative communication systems by means of improving the source and relay precoders by taking relay and direct links into consideration. Simulation outcomes prove that the EE‐ EBO optimization is capable of enhancing the outcomes of MIMO‐AF systems while matched up with direct/relay link with EE precoding optimization and precoding optimization algorithms.

show abstract