Performance Trade-off Between Uplink and Downlink in Full-Duplex Communications

In this paper, we formulate two multi-objective optimization problems (MOOPs) in orthogonal frequency-division multiple access (OFDMA)-based in-band full-duplex (IBFD) wireless communications.~The aim of this study is to exploit the performance trade-off between uplink and downlink where a wireless radio simultaneously transmits and receives in the same frequency.~We consider maximizing the system throughput as the first MOOP and minimizing the system aggregate power consumption as the second MOOP between uplink and downlink,~while taking into account the impact of self-interference~(SI)~and quality of service provisioning.~We study the throughput and the transmit power trade-off between uplink and downlink via solving these two problems.~Each MOOP is a non-convex mixed integer non-linear programming~(MINLP)~which is generally intractable. In order to circumvent this difficulty, a penalty function is introduced to reformulate the problem into a mathematically tractable form.~Subsequently,~each MOOP is transformed into a single-objective optimization problem~(SOOP)~via the weighted Tchebycheff method which is addressed by majorization-minimization~(MM)~approach. Simulation results demonstrate an interesting trade-off between the considered competing objectives.Comment: This paper is accepted by IEEE International Conference on Communications (ICC

Interference management with reflective in-band full-duplex NOMA for secure 6G wireless communication systems

The electromagnetic spectrum is used as a medium for modern wireless communication. Most of the spectrum is being utilized by the existing communication system. For technological breakthroughs and fulfilling the demands of better utilization of such natural resources, a novel Reflective In-Band Full-Duplex (R-IBFD) cooperative communication scheme is proposed in this article that involves Full-Duplex (FD) and Non-Orthogonal Multiple Access (NOMA) technologies. The proposed R-IBFD provides efficient use of spectrum with better system parameters including Secrecy Outage Probability (SOP), throughput, data rate and secrecy capacity to fulfil the requirements of a smart city for 6th Generation (6thG or 6G). The proposed system targets the requirement of new algorithms that contribute towards better change and bring the technological revolution in the requirements of 6G. In this article, the proposed R-IBFD mainly contributes towards co-channel interference and security problem. The In-Band Full-Duplex mode devices face higher co-channel interference in between their own transmission and receiving antenna. R-IBFD minimizes the effect of such interference and assists in the security of a required wireless communication system. For a better understanding of the system contribution, the improvement of secrecy capacity and interference with R-IBFD is discussed with the help of SOP derivation, equations and simulation results. A machine learning genetic algorithm is one of the optimization tools which is being used to maximize the secrecy capacity

Joint Power Allocation and Beamforming for In-band Full-duplex Multi-cell Multi-user Networks

This paper investigates a robust joint power allocation and beamforming scheme for in-band full-duplex multicell multi-user (IBFD-MCMU) networks. A mean-squared error (MSE) minimization problem is formulated with constraints on the power budgets and residual self-interference (RSI) power. The problem is not convex, so we decompose it into two sub-problems: interference management beamforming and power allocation, and give closed-form solutions to the sub-problems. Then we propose an iterative algorithm to yield an overall solution. The computational complexity and convergence behavior of the algorithm are analyzed. Our method can enhance the analog selfinterference cancellation (ASIC) depth provided by the precoder with less effect on the downlink communication than the existing null-space projection method, inspiring a low-cost but efficient IBFD transceiver design. It can achieve 42.9% of IBFD gain in terms of spectral efficiency with only antenna isolation, while this value increases to 60.9% with further digital selfinterference cancellation (DSIC). Numerical results illustrate that our algorithm is robust to hardware impairments and channel uncertainty. With sufficient ASIC depth, our method reduces the computation time by at least 20% than the existing scheme due to its faster convergence speed at the cost of < 12.5% sum rate loss. The benefit is much more significant with single-antenna users that our algorithm saves at least 40% of the computation time at the cost of < 10% sum rate reduction

Energy and Spectral Efficiency Tradeoff in OFDMA Networks via Antenna Selection Strategy

In this paper, we investigate the joint resource allocation and antenna selection algorithm design for uplink orthogonal frequency division multiple access (OFDMA) communication system. We propose a multi-objective optimization framework to strike a balance between spectral efficiency (SE) and energy efficiency (EE). The resource allocation design is formulated as a multi-objective optimization problem (MOOP), where the conflicting objective functions are linearly combined into a single objective function employing the weighted sum method. In order to develop an efficient solution, the majorization minimization (MM) approach is proposed where a surrogate function serves as a lower bound of the objective function. Then an iterative suboptimal algorithm is proposed to maximize the approximate objective function. Numerical results unveil an interesting tradeoff between the considered conflicting system design objectives and reveal the improved EE and SE facilitated by the proposed transmit antenna selection in OFDMA systems.Comment: This paper is Accepted by IEEE Wireless Communications and Networking Conference (WCNC