Various Expressions over Novel k-µ/Inverse Gamma LOS Shadowed Fading

Shilpi Gadi, S. Pratap Singh, Sanjay Kumar, Ghanshyam Singh, Anurag Singh Baghel

Research output: Contribution to journalArticlepeer-review


This manuscript proposes a novel, very general shadowed k-μ fading model for characterizing the realistic line-of-sight (LOS) propagation scenarios of 5G and beyond. In this model, statistics of the received signal are manifested by the clustering of multipath components. Within each of these clusters, shadowing of the dominant component is represented by the inverse Gamma distribution. First of all, mathematically-tractable expressions of probability density function (PDF) and moment-generating function (MGF) of the k-μ/inverse Gamma LOS-shadowed fading model are obtained. The proposed channel model is validated by reproducing the well-established fading distributions such as Rayleigh, Rice (Nakagami-n) and Nakagami-m under light shadowing conditions and LOS-shadowed fading distributions such as the k-µ/Gamma and Abdi’s Rice/Gamma model under heavy shadowing conditions numerically. The proposed PDF is further utilized to derive the expressions for channel capacity under optimal rate adaptation with constant transmit power (CORA), optimal power and rate adaptation (COPRA), channel inversion with fixed rate (CCIFR) and truncated channel inversion (CCIFR). Furthermore, analytical expressions for outage probability (OP) and error probabilities under different modulation schemes are derived. The analytical expressions are studied under infrequent light, moderate, and frequent heavy shadowing environments used extensively in literature.

Original languageEnglish
Pages (from-to)1863-1886
Number of pages24
JournalWireless Personal Communications
Issue number3
Publication statusPublished - Oct 2023


  • Adaptation policies
  • Capacity
  • Error probabilities
  • Inverse Gamma distribution
  • LOS shadowing

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


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