Abstract
The Partial Transmit Sequence which reduces the PAPR (Peak-to-Average Power Ratio) in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system using a novel optimization algorithm is proposed in this study. This novel optimization algorithm is based on a hybrid of Bacterial Foraging Optimization (BFO) and Modified Cuckoo Search algorithm (MCS) and is thus called HBFOMCS. In HBFOMCS, reproduction of individuals in a new generation is created, not only by swim and tumble operation as in BFO, but also by MCS. The natural reproduction step of BFO is swapped by the concept of searching best solutions as in MCS which then increases the possibility of generating the elite individuals for next generation. These enhanced reproduction step constitute the ready-to-perform population for the new generation once the initial population is performed by swim and tumble operation. Afterwards, discover probability is applied to abandon the worst solution due to the nature of MCS. HBFOMCS is applied to optimize the best combination from a set of allowed phase factors in Partial Transmit Sequence (PTS) technique. The performance of HBFOMCS is compared with BFO, Cuckoo Search (CS) and Modified cuckoo search MCS in the PAPR reduction in MIMO-OFDM system, accordingly proving its proficiency.
Highlights
The advent evolutionary computation has inspired new resources for optimization problem solving, such as the optimal algorithms for phase factor optimization in Partial transmit sequence of MIMO-OFDM systems
We propose a new algorithm that combines the evolution ideas of both Bacterial Foraging Optimization (BFO) and Modified Cuckoo Search (MCS)
Hybrid BFOMCS algorithm is applied to search the better combination of phase factor for Partial Transmit Sequence (PTS)
Summary
The advent evolutionary computation has inspired new resources for optimization problem solving, such as the optimal algorithms for phase factor optimization in Partial transmit sequence of MIMO-OFDM systems. In order to get the OFDM signals with the minimum PAPR, a suboptimal combination method based on the hybrid of Bacterial Foraging (BFO) and Modified Cuckoo Search (MCS) algorithm is proposed to solve the optimization problem of PTS. Population or initialization Swim and tumble Reproduction with Lévy flight This hybrid optimization algorithm utilizes the capable properties of MCS in BFO algorithm to achieve the better search ability with less computational complexity. HBFOMCS algorithm: A ← Max Lévy Step Size MaxTumble ← Allowed tumble steps MaxSwim ← Allowed swim steps Pd ← Discover Probability Ps = 1 - Pd ← Select Probability S ← Split Position Initialize a population of n nests: xi (i = 1, 2,..., n) for all xi do Calculate fitness Fi = f (xi) end for Generation number G←1 while G≤Gmax do.
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