[Paper Review] Optimal Transmit Power Allocation for MIMO Two-Way Cognitive Relay Networks with Multiple Relays

Ahmad Alsharoa, Hakim Ghazzai+1 more|arXiv (Cornell University)|Sep 29, 2013

Cooperative Communication and Network Coding8 references3 citations

TL;DR

This paper proposes an optimal power allocation scheme for MIMO two-way cognitive relay networks with multiple amplify-and-forward relays, maximizing secondary sum rate under primary user interference and transmit power constraints. The analytical solution, derived using convex optimization, shows that increasing antennas or relays significantly boosts spectral efficiency, with 180% rate gain observed when using four antennas instead of one under high power constraints.

ABSTRACT

In this letter, we consider a multiple-input multiple-output two-way cognitive radio system under a spectrum sharing scenario, where primary and secondary users operate on the same frequency band. The secondary terminals aims to exchange different messages with each other using multiple relays where each relay employs an amplify-and-forward strategy. The main objective of our work is to maximize the secondary sum rate allowed to share the spectrum with the primary users by respecting a primary user tolerated interference threshold. In this context, we derive a closed-form expression of the optimal power allocated to each antenna of the terminals. We then discuss the impact of some system parameters on the performance in the numerical result section.

Motivation & Objective

• To maximize the secondary sum rate in a MIMO two-way cognitive relay network with multiple amplify-and-forward relays.
• To ensure primary user quality of service by imposing an interference threshold constraint on the secondary network.
• To derive a closed-form analytical solution for optimal power allocation across individual antennas at secondary terminals.
• To investigate the impact of system parameters such as relay number, antenna count, and power budgets on performance.

Proposed method

• Formulates a constrained optimization problem to maximize secondary sum rate under peak power and interference threshold constraints.
• Uses Lagrangian relaxation and Karush-Kuhn-Tucker (KKT) conditions to derive the optimal power allocation per antenna.
• Derives analytical expressions for optimal transmit power at each terminal antenna, given by equation (12), based on channel state information and Lagrange multipliers.
• Assumes full channel state information (CSI) at terminals and uses unitary precoding and decoding matrices to align signals.
• Models interference from secondary relays and terminals on the primary user, with constraints on average interference power.
• Analyzes performance via numerical simulations under varying system parameters such as relay amplification factor, number of relays, and antenna configurations.

Experimental results

Research questions

• RQ1 How can the secondary sum rate be maximized in a MIMO two-way cognitive relay network with multiple amplify-and-forward relays under primary interference constraints?
• RQ2 What is the optimal power allocation strategy per antenna at secondary terminals to achieve maximum sum rate while respecting power and interference limits?
• RQ3 How do system parameters such as the number of relays, relay amplification factor, and number of antennas affect the achievable sum rate?
• RQ4 What is the impact of increasing the number of relays versus increasing the number of antennas on spectral efficiency?
• RQ5 How does the optimal relay amplification factor vary with changes in transmit power, relay power, and interference threshold?

Key findings

• The derived analytical solution for optimal power allocation (equation 12) closely matches simulation results, validating the theoretical model.
• Increasing the number of relays from 2 to 6 improves the secondary sum rate by up to 180% when using four antennas instead of one, under high peak power constraints.
• The optimal relay amplification factor (wopt) decreases as the peak transmit power (¯Pt) increases, to satisfy interference and power constraints.
• Increasing the relay power budget (¯Pr) increases the optimal amplification factor wopt, enhancing system sum rate.
• Adding relays has a more significant impact on sum rate than adding antennas, due to increased spatial diversity and degrees of freedom.
• Raising the interference threshold (Ith) increases the achievable sum rate without altering the optimal amplification factor, as long as power budgets remain fixed.