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Energy Efficiency Maximization in the Uplink Delta-OMA Networks

Ramin Hashemi, Hamzeh Beyranvand, Mohammad Robat Mili, Ata Khalili, Hina Tabassum, Derrick Wing Kwan Ng

TL;DR

A multi-objective optimization framework to maximize the uplink energy efficiency in a multi-cell network enabled by D-OMA is developed and numerical results show that D- OMA outperforms the conventional non-orthogonal multiple access (NOMA) and orthogonal frequency divisionmultiple access (OFDMA) when the adjacent sub-channel overlap and scheduling is optimized jointly.

Abstract

Delta-orthogonal multiple access (D-OMA) has been recently investigated as a potential technique to enhance the spectral efficiency in the sixth-generation (6G) networks. D-OMA enables partial overlapping of the adjacent sub-channels that are assigned to different clusters of users served by non-orthogonal multiple access (NOMA), at the expense of additional interference. In this paper, we analyze the performance of D-OMA in the uplink and develop a multi-objective optimization framework to maximize the uplink energy efficiency (EE) in a multi-access point (AP) network enabled by D-OMA. Specifically, we optimize the sub-channel and transmit power allocations of the users as well as the overlapping percentage of the spectrum between the adjacent sub-channels. The formulated problem is a mixed binary non-linear programming problem. Therefore, to address the challenge we first transform the problem into a single-objective problem using Tchebycheff method. Then, we apply the monotonic optimization (MO) to explore the hidden monotonicity of the objective function and constraints, and reformulate the problem into a standard MO in canonical form. The reformulated problem is then solved by applying the outer polyblock approximation method. Our numerical results show that D-OMA outperforms the conventional non-orthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA) when the adjacent sub-channel overlap and scheduling are optimized jointly.

Energy Efficiency Maximization in the Uplink Delta-OMA Networks

TL;DR

A multi-objective optimization framework to maximize the uplink energy efficiency in a multi-cell network enabled by D-OMA is developed and numerical results show that D- OMA outperforms the conventional non-orthogonal multiple access (NOMA) and orthogonal frequency divisionmultiple access (OFDMA) when the adjacent sub-channel overlap and scheduling is optimized jointly.

Abstract

Delta-orthogonal multiple access (D-OMA) has been recently investigated as a potential technique to enhance the spectral efficiency in the sixth-generation (6G) networks. D-OMA enables partial overlapping of the adjacent sub-channels that are assigned to different clusters of users served by non-orthogonal multiple access (NOMA), at the expense of additional interference. In this paper, we analyze the performance of D-OMA in the uplink and develop a multi-objective optimization framework to maximize the uplink energy efficiency (EE) in a multi-access point (AP) network enabled by D-OMA. Specifically, we optimize the sub-channel and transmit power allocations of the users as well as the overlapping percentage of the spectrum between the adjacent sub-channels. The formulated problem is a mixed binary non-linear programming problem. Therefore, to address the challenge we first transform the problem into a single-objective problem using Tchebycheff method. Then, we apply the monotonic optimization (MO) to explore the hidden monotonicity of the objective function and constraints, and reformulate the problem into a standard MO in canonical form. The reformulated problem is then solved by applying the outer polyblock approximation method. Our numerical results show that D-OMA outperforms the conventional non-orthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA) when the adjacent sub-channel overlap and scheduling are optimized jointly.

Paper Structure

This paper contains 10 sections, 1 theorem, 10 equations, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Network Rate and Energy Efficiency
  5. Multi-objective Problem Formulation
  6. Problem Transformation and Solution
  7. Problem Transformation
  8. Solution Approach (Monotonic Optimization)
  9. Numerical Results
  10. Conclusion

Key Result

Theorem 1

The following optimization problem where $\boldsymbol{\Xi}$, $\boldsymbol{\Xi}_c$ denote the normal and co-normal sets, respectively and $f(.)$ and $g(.)$ are both increasing functions in $[\textbf{0},\textbf{b}]$ is a class of monotonic optimization problem.

Figures (4)

  • Figure 1: The UL D-OMA transmission.
  • Figure 2: Total SE and SP for different multiple access schemes.
  • Figure 3: Total EE versus SE.
  • Figure 4: Total network SE versus total number of the UEs.

Theorems & Definitions (2)

  • Theorem 1
  • proof