Evolutionary Game for Hybrid Uplink NOMA With Truncated Channel Inversion Power Control

Abstract

In this paper, we consider hybrid uplink nonorthogonal multiple access (NOMA) that can support more users by exploiting the notion of power-domain NOMA. In hybrid uplink NOMA, we do not consider centralized power control as a base station (BS) needs instantaneous channel state information (CSI) of all users which leads to a high signaling overhead. Rather, each user is allowed to perform power control under fading in accordance with a truncated channel inversion power control policy. Due to the lack of coordination of centralized power control, users in the same resource block compete for access. To analyze users' behavior, evolutionary game can be considered so that each user can choose transmission strategies to maximize payoff in hybrid uplink NOMA with power control. Evolutionarily stable strategy (ESS) is characterized with fixed costs as well as costs that depend on channel realizations, and it is also shown that hybrid uplink NOMA can provide a higher throughput than orthogonal multiple access (OMA). To update the state in evolutionary game for hybrid uplink NOMA, the replicator dynamic equation is considered with two possible implementation methods.

Performance Analysis of Uplink NOMA With Constellation–Rotated STLC for IoT Networks

“…Based on the same approach as (11), this proves that the spatial diversity order is two. The same result is also given when G 2 ≥ 0, so we can state that the diversity order of the PEP, Pr(x i → x j ), is greater than or equal to two (exactly two due to the degrees of freedom) when…”

“…assume that x n,1 = x n,1 for 1 ≤ n ≤ K and x n,1 = x n,1 for K < n ≤ N . Note that we have proved from (11) that the uplink CR-STLC NOMA system achieves the optimal diversity order of two when K = 2. Let…”

“…(11) From (11), it is clear that the uplink CR-STLC NOMA achieves the optimal spatial diversity order of two for both STAs when there are two STAs, which is the same as the OMA with two receive antennas in the AP.…”

“…However, in massive IoT networks, it seems infeasible for an AP to obtain full CSI from a massive number of IoT devices (stations: STAs) to itself due to significant signaling overhead [10], [11]. Instead, each STA can easily obtain its CSI from itself to the AP by observing the downlink common pilot signal broadcast from the AP, considering the channel reciprocity property in the time-division duplex (TDD) system [3], [12], which is a dominant frame structure of contemporary commercial wireless systems including the third generation partnership project (3GPP) 5G new radio (NR) [13], [14].…”

On Asymmetric Game for NOMA-ALOHA under Fading

“…To understand the performance of random access, game theory is often employed [7] [8] [9]. When NOMA is applied to ALOHA [10] for MTC as in [11] [12], which results in NOMA-ALOHA, the model based on non-cooperative game theory can be used to understand its performance. While noncooperative game theory is a tool to see the behaviors of players (i.e., devices and sensors that compete for access in random access), it can also be used to derive learning rules for interacting players [13] [14].…”