# US 11,444,730 B2 · Bandwidth part (BWP) and power scheduling method and apparatus for indoor terahertz

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- Number: US 11,444,730 B2
- Document ID: US11444730B2
- Status: Granted
- Kind: B2
- Application number: 17/138,949
- Filed: 2020-12-31
- Published: 2022-05-05
- Granted: 2022-09-13
- Earliest claimed: 2020-10-29
- Assignees: University of Science and Technology Beijing
- Applicants: University of Science and Technology Beijing
- Inventors: Haijun Zhang; Xiangnan Liu; Keping Long
- Web page: https://patentgrep.com/patent/US11444730B2

## CPC

- H04L 5/0023: {Time-frequency-space}
- H04W 52/242: {taking into account path loss}
- H04L 5/001: {the frequencies being arranged in component carriers}
- H04L 5/0037: {Inter-user or inter-terminal allocation}
- H04L 5/006: {Quality of the received signal, e.g. BER, SNR, water filling}
- H04W 52/346: {distributing total power among users or channels}
- H04W 52/50: at the moment of starting communication in a multiple access environment
- H04W 72/53: based on regulatory allocation policies
- H04W 72/535: {based on resource usage policies}
- H04W 72/542: using measured or perceived quality
- H04W 72/0453: Resources in frequency domain, e.g. a carrier in FDMA
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)

## Abstract

A bandwidth part (BWP) and power scheduling method and apparatus for indoor terahertz are provided. The BWP and power scheduling method uses an intelligent reflecting surface (IRS) and a non-orthogonal multiple access (NOMA) to compensate for a shortcoming, wherein terahertz waves are not suitable for an indoor transmission, convert an indoor environment of an IRS-assisted terahertz propagation into a channel model, and convert an optimal wireless resource scheduling in an indoor IRS-assisted terahertz system into a functional optimization design with random constraints. Policies and corresponding actions are trained by using a proximal policy optimization (PPO) to schedule a power and a BWP. An actor part generates continuous a power scheduling, and a critic part generates a discrete BWP scheduling.

## Claims

### Claim 1

A bandwidth part (BWP) and power scheduling method for an indoor terahertz, comprising the following steps:
S1: initializing parameters and states of a wireless access device, users, and an intelligent reflecting surface (IRS), wherein the parameters comprises an initial transmit power p0, a policy parameter θ0:={μ0,σ0}, and Lagrange multipliers λ0,ϕ0, wherein μ0 denotes expectation of an initial policy, and σ0 denotes variance of the initial policy;
S2: extracting samples {circumflex over (x)}1, {circumflex over (x)}2, {circumflex over (θ)} a truncated standard normal distribution;
S3: calculating a terahertz path loss L(ƒ,d) and a channel gain hj,k, wherein paths comprises a first transmission path from the wireless access device to each user, and a second transmission path from the wireless access device to the each user through a reflection by the IRS, and wherein ƒ denotes carrier frequency, and d denotes distance, j denotes an index of an antenna of an access point, k denotes an index of a current user;
S4: inputting initial conditions to a resource scheduling formula;
S5: inputting a channel state obtained from a channel state matrix HJK to a proximal policy optimization (PPO) algorithm, wherein J denotes a number of antennas, and K denotes a number of users;
S6: calculating an estimate of a gradient according to an obtained new policy parameter set θ and a generated scheduling action;
S7: updating primal-dual variables by using a primal-dual optimization algorithm, until a reward converges;
S8: outputting an action obtained after learning, a scheduled BWP factor β and a power p, and a final system performance function ƒ0(x), wherein x denotes an ergodic mean;
S9: traversing the users, and repeating step S2 to step S7, to complete a scheduling for the users; and
S10: terminating the BWP and power scheduling method process, and fetching data.

### Claim 2 (depends on 1)

The BWP and power scheduling method according to claim 1, wherein in step S3, channel estimations are integrated:
Hj,k≙HLOS,j,k+Hj,rΦHr,k,
to unify the first transmission path and the second transmission path;
wherein Hj,k is a first channel gain from the wireless access device to the each user, Hr,k is a second channel gain from the IRS to the each user, Hj,r is a third channel gain from the wireless access device to the IRS, Φ is a phase transition matrix, and HLOS,j,k is a fourth channel gain without passing through the IRS.

### Claim 3 (depends on 1)

The BWP and power scheduling method according to claim 1, wherein in step S4, the resource scheduling formula is expressed as a long-term instantaneous system performance function using the ergodic mean x capture system: x≤E[f(p(h),h)], wherein f(p(h),h) is an instantaneous performance function, wherein h denotes a channel state.

### Claim 4 (depends on 1)

The BWP and power scheduling method according to claim 1, wherein in step S5, the channel state is inputted to an actor part and a critic part of the PPO algorithm, wherein the actor part generates a new policy function, and selects a Gaussian policy to output a choice for scheduling of the action, and the critic part generates a new action according to an original Q value function, to schedule a BWP factor.

### Claim 5 (depends on 1)

The BWP and power scheduling method according to claim 1, wherein in step S6, the estimate of the gradient is calculated according to the obtained new policy parameter set θ and the generated scheduling action:
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