Resource Allocation for Symbiotic Radio System With Fading Channels

Abstract

In this paper, we investigate the resource allocation problem for the symbiotic radio system, in which the passive backscatter transmission is parasitic in the primary transmission, and the cooperative receiver simultaneously detects the signals transmitted from the active primary transmitter (PT) and the backscatter device (BD). In particular, channel fading is considered, and the ergodic weighted sum rate of the primary and backscatter transmissions is maximized by jointly optimizing the transmit power at the PT and the reflection coefficient at the BD under either long-term or short-term transmit-power constraint over the fading states. Two practical transmission setups are considered, where the relationship between the primary and backscatter transmissions is either commensal or parasitic. For the commensal setup, we fix the reflection coefficient as the maximum value and derive the optimal power allocation scheme based on the standard convex optimization procedure. For the parasitic setup, the weighted sum-rate maximization problem is non-convex, and we resort to the concave-convex procedure to derive a suboptimal solution. Simulation results demonstrate that in the commensal setup, the BD may realize transmission while causing no harmful interference to the primary system; in the parasitic setup, a higher backscatter data rate can be achieved through slightly sacrificing the primary transmission rate. INDEX TERMS Internet of Things, ambient backscatter communications, symbiotic radio, ergodic rate, spectrum sharing, fading channel.

Resource Allocations for Symbiotic Radio With Finite Blocklength Backscatter Link

“…, which follows the noncentral chi-square distribution two degrees of freedom [2], [15]. Its PDF is given by…”

“…Thus, we consider an asymptotic approximation at the high SNR regime. When, the SNR is sufficient large, we have the closed-form expression for the average rate r u as [2], [15]…”

“…Recently, the SR system has attracted increasing attention [15]- [20]. In [15], a resource allocation scheme in the SR system was investigated in the fading channel, where the power allocation at the primary transmitter (PT) and the reflection coefficient at the BD are jointly designed to maximize the ergodic weighted sum rate of the direct and backscatter links in the long-term and short-term transmit power budget over the fading states, respectively.…”

“…Recently, the SR system has attracted increasing attention [15]- [20]. In [15], a resource allocation scheme in the SR system was investigated in the fading channel, where the power allocation at the primary transmitter (PT) and the reflection coefficient at the BD are jointly designed to maximize the ergodic weighted sum rate of the direct and backscatter links in the long-term and short-term transmit power budget over the fading states, respectively. The authors in [16] investigated resource allocation scheme in a novel SR paradigm, i.e., cooperative AmBC, where three practical SR schemes (i.e., commensal, parasitic, and competitive) have been exploited, respectively, to derive the achievable rates for both direct and backscatter links for the fading state.…”

Intelligent User Association for Symbiotic Radio Networks Using Deep Reinforcement Learning

“…To support massive IoT connections, it is highly desirable to design spectrum-, energy-, and infrastructure-efficient communication technologies. Symbiotic radio networks (SRN) [4]- [6], in which an IoT network parasitizes in a primary network, is envisioned as a promising technique to achieve this goal. In addition, when ambient backscatter communication (AmBC) [7] is used for IoT transmission, the IoT devices in SRN transmit their messages to theirs destinations by reflecting the signals received from the primary transmitter without requiring active radio-frequency (RF) transmitter chain.…”