研究目的
To maximize the total system goodput by jointly optimizing reader transmission power, time allocation, and re?ection ratio for the cases of passive and semi-passive tags in a backscatter communication system.
研究成果
The proposed resource allocation policies for multi-user BackCom systems, considering both passive and semi-passive tags, demonstrate superior performance in maximizing the total system goodput. The optimal policy for passive tags and a close-to-optimal solution for semi-passive tags are derived, with simulation results confirming their effectiveness. The study highlights the importance of optimizing reader transmission power, time allocation, and re?ection ratio to enhance system performance.
研究不足
The study assumes perfect self-interference cancellation at the reader and perfect knowledge of channel gain information by the reader and tags, which may not be feasible in realistic scenarios. Additionally, the optimization problems are non-convex, making it challenging to find global optimal solutions.
1:Experimental Design and Method Selection:
The study involves formulating optimization problems for both passive and semi-passive tags cases, which are non-convex and decomposed into feasible sub-problems. Convex optimization techniques and a block coordinate descent (BCD)-based optimization algorithm are employed to solve these problems.
2:Sample Selection and Data Sources:
The system model includes a reader and N tags, with channel gains modeled as free-space channels and reciprocal. The channel gain information is assumed to be perfectly known.
3:List of Experimental Equipment and Materials:
The simulation environment includes parameters such as time duration, distance, channel gains, energy harvesting efficiency, maximum BER, circuit power, and noise power.
4:Experimental Procedures and Operational Workflow:
The study involves solving optimization problems for both passive and semi-passive tags cases, comparing their maximum total goodput, and validating the proposed policies through simulation results.
5:Data Analysis Methods:
The performance metric, total goodput, is analyzed based on the successful transmission bits of each symbol in the active state, considering the quality of service (QoS) constraints.
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