HARQ with chase-combining for bandwidth-efficient communication in MIMO wireless networks

Prior works either considered outage capacity of wireless video transmission systems but did not consider NOMA which is a key technology for 5G ultra-reliable low-latency (URLLC), or concerned the ergodic capacity of NOMA-OFDMA systems but did not consider the outage capacity emphasized in 5G URLLC scenario. In this paper, outage capacity (as well as ergodic capacity) maximization in a 5G URLLC scenario, are considered, using two proposed resource management schemes (i.e. B, C) and finally, proposed deep-learning-based versions of Schemes B and C (i.e. Schemes B' and C') to reduce the complexity and the latency for 5G URLLC. The proposed schemes re-allocate subcarrier according to outage capacityinstead of ergodic capacity only-maximization objective and choose the candidate user to gain subcarrier in a new way to improve the outage capacity. The numerical results show the proposed Scheme B and C increase the outage capacity (the percentage of satisfied users) from 79.2% for a prior work (Scheme A) to 85.2% and 92.6%, respectively. Scheme C also increases the ergodic capacity (average PSNR) from 34.7dB for Scheme A to 35.5dB. The deep learning based Schemes B' and C' perform slightly poorer than the corresponding non deep learning based Schemes B and C but the execution time/latency of Scheme B'/C' is less than Schemes B/C.

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“…The proposed schemes do not consider multiple-antennas as [61] [62]. Removing these limitations is the goal of our future works.…”

Section: Discussionmentioning

confidence: 99%

Outage-Capacity-Based Cross Layer Resource Management for Downlink NOMA-OFDMA Video Communications: Non-Deep Learning and Deep Learning Approaches

Tseng

Tsai

Yu³

2020

IEEE Access

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“…ALGORITHM 1 The blind identification algorithm for the feedback polynomial of the synchronous scrambler.…”

Section: The Length Of the Scrambled Sequence Required To Complete Th...mentioning

confidence: 99%

“…In a general communication system, the receiver knows the communication protocol and the relevant parameters of the transmitter. Therefore, the main research lies in discovering better techniques to achieve high-speed data transmission with low Bit Error Rate, increased channel capacity, and bandwidth efficiency [1]. In non-cooperative conditions, such as spectrum surveillance and cognitive radio, the receiver must blindly estimate the parameters used in the transmitter without prior knowledge of the transmitter to recover the information.…”

Section: Introductionmentioning

confidence: 99%

Blind identification of feedback polynomials for synchronous scramblers in a noisy environment

2022

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This paper investigates blind identification methods for linear scramblers under non‐cooperative conditions, which are essential for the inverse analysis of communication protocols using scramblers. In this paper, a blind identification scheme for feedback polynomials of synchronous scramblers is proposed. A variable Υ¯$\overline{\Upsilon }$ is first proposed that measures the correctness of the test polynomial by using the soft information of the received sequence, then the mean and variance of the variable Υ¯$\overline{\Upsilon }$ in different cases are obtained, and finally the optimal threshold value to determine whether the test primitive polynomial is correct or not is obtained. That is, the blind identification problem is transformed into a hypothesis testing problem. The simulations verify that the proposed scheme requires a much smaller scrambled sequence length than existing blind identification schemes. Furthermore, the proposed scheme is more fault tolerant than existing schemes and has a signal‐to‐noise ratio (SNR) gain of at least 3 dB when the intercepted scrambled sequences are of the same length and high identification accuracy is achieved.

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“…Furthermore, considering m-MIMO systems with a terahertz (THz) frequency is also worth investigating in future. Finally, evaluating the m-MIMO using a hybrid automatic repeat request for spatial multiplexing transmission systems, as in [53], may also be considered in future.…”

Section: Concluding Remarks and Future Research Directionsmentioning

confidence: 99%

The Role of Correlation in the Performance of Massive MIMO Systems

Naser

Salman

Alsabah

2021

ASI

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Massive multiple-input multiple-output (m-MIMO) is considered as an essential technique to meet the high data rate requirements of future sixth generation (6G) wireless communications networks. The vast majority of m-MIMO research has assumed that the channels are uncorrelated. However, this assumption seems highly idealistic. Therefore, this study investigates the m-MIMO performance when the channels are correlated and the base station employs different antenna array topologies, namely the uniform linear array (ULA) and uniform rectangular array (URA). In addition, this study develops analyses of the mean square error (MSE) and the regularized zero-forcing (RZF) precoder under imperfect channel state information (CSI) and a realistic physical channel model. To this end, the MSE minimization and the spectral efficiency (SE) maximization are investigated. The results show that the SE is significantly degraded using the URA topology even when the RZF precoder is used. This is because the level of interference is significantly increased in the highly correlated channels even though the MSE is considerably minimized. This implies that using a URA topology with relatively high channel correlations would not be beneficial to the SE unless an interference management scheme is exploited.

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HARQ with chase-combining for bandwidth-efficient communication in MIMO wireless networks

Cited by 11 publications

References 25 publications

Outage-Capacity-Based Cross Layer Resource Management for Downlink NOMA-OFDMA Video Communications: Non-Deep Learning and Deep Learning Approaches

Outage-Capacity-Based Cross Layer Resource Management for Downlink NOMA-OFDMA Video Communications: Non-Deep Learning and Deep Learning Approaches

Blind identification of feedback polynomials for synchronous scramblers in a noisy environment

The Role of Correlation in the Performance of Massive MIMO Systems

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