اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدNOMA in the Uplink: Delay Analysis with Imperfect CSI and Finite-Length Coding
117
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We study whether using non-orthogonal multiple access (NOMA) in the uplink of a mobile network can improve the performance over orthogonal multiple access (OMA) when the system requires ultra-reliable low-latency communications (URLLC). To answer this question, we first consider an ideal system model with perfect channel state information (CSI) at the transmitter and long codewords, where we determine the optimal decoding orders when the decoder uses successive interference cancellation (SIC) and derive closed-form expressions for the optimal rate when joint decoding is used. While joint decoding performs well even under tight delay constraints, NOMA with SIC decoding often performs worse than OMA. For low-latency systems, we must also consider the impact of finite-length channel coding, as well as rate adaptation based imperfect CSI. We derive closed-form approximations for the corresponding outage or error probabilities and find that those effects create a larger performance penalty for NOMA than for OMA. Thus, NOMA with SIC decoding may often be unsuitable for URLLC.
قيم البحث
اقرأ أيضاً
In this paper, we present the ergodic sum secrecy rate (ESSR) analysis of an underlay spectrum sharing non-orthogonal multiple access (NOMA) system. We consider the scenario where the power transmitted by the secondary transmitter (ST) is constrained
by the peak tolerable interference at multiple primary receivers (PRs) as well as the maximum transmit power of the ST. The effect of channel estimation error is also taken into account in our analysis. We derive exact and asymptotic closed-form expressions for the ESSR of the downlink NOMA system, and show that the performance can be classified into two distinct regimes, i.e., it is dictated either by the interference constraint or by the power constraint. Our results confirm the superiority of the NOMA-based system over its orthogonal multiple access (OMA) based counterpart. More interestingly, our results show that NOMA helps in maintaining the secrecy rate of the strong user while significantly enhancing the secrecy performance of the weak user as compared to OMA. The correctness of the proposed investigation is corroborated through Monte Carlo simulation.
In this paper, approximate outage probability (OP) expressions are derived for uplink cell-free massive multiple-input-multiple-output (CF-mMIMO) system. The access points (APs) of the system considered have imperfect channel state information (CSI).
The approximate expressions are derived first using conditional expectations and then using a novel dimension reduction method that approximates higher-order integration by several single order integrations. Using the same approach, closed-form approximations are also derived for conventional massive MIMO (mMIMO) systems. The OP approximations are then used to characterize the performance of cell-edge users of CF-mMIMO systems and compare the designs of CF-mMIMO and mMIMO systems. The derived expressions have a close match with the simulated expression for OP.
In this paper, the design of robust linear precoders for the massive multi-input multi-output (MIMO) downlink with imperfect channel state information (CSI) is investigated. The imperfect CSI for each UE obtained at the BS is modeled as statistical C
SI under a jointly correlated channel model with both channel mean and channel variance information, which includes the effects of channel estimation error, channel aging and spatial correlation. The design objective is to maximize the expected weighted sum-rate. By combining the minorize-maximize (MM) algorithm with the deterministic equivalent method, an algorithm for robust linear precoder design is derived. The proposed algorithm achieves a stationary point of the expected weighted sum-rate maximization problem. To reduce the computational complexity, two low-complexity algorithms are then derived. One for the general case, and the other for the case when all the channel means are zeros. For the later case, it is proved that the beam domain transmission is optimal, and thus the precoder design reduces to the power allocation optimization in the beam domain. Simulation results show that the proposed robust linear precoder designs apply to various mobile scenarios and achieve high spectral efficiency.
We consider a two-way half-duplex relaying system where multiple pairs of single antenna users exchange information assisted by a multi-antenna relay. Taking into account the practical constraint of imperfect channel estimation, we study the achievab
le sum spectral efficiency of the amplify-and-forward (AF) and decode-and-forward (DF) protocols, assuming that the relay employs simple maximum ratio processing. We derive an exact closed-form expression for the sum spectral efficiency of the AF protocol and a large-scale approximation for the sum spectral efficiency of the DF protocol when the number of relay antennas, $M$, becomes sufficiently large. In addition, we study how the transmit power scales with $M$ to maintain a desired quality-of-service. In particular, our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to $1/M^alpha$, $1/M^beta$, and $1/M^gamma$ for certain $alpha$, $beta$, and $gamma$, respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum spectral efficiency, novel power allocation schemes are designed to further improve the sum spectral efficiency.
In this paper, we investigate a non-orthogonal multiple access (NOMA) based mobile edge computing (MEC) network, in which two users may partially offload their respective tasks to a single MEC server through uplink NOMA. We propose a new offloading s
cheme that can operate in three different modes, namely the partial computation offloading, the complete local computation, and the complete offloading. We further derive a closed-form expression of the successful computation probability for the proposed scheme. As part of the proposed offloading scheme, we formulate a problem to maximize the successful computation probability by jointly optimizing the time for offloading, the power allocation of the two users and the offloading ratios which decide how many tasks should be offloaded to the MEC server. We obtain the optimal solutions in the closed forms. Simulation results show that our proposed scheme can achieve the highest successful computation probability than the existing schemes.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
