The integration of solar energy harvesting into small-cell networks is a promising solution for achieving energy-efficient and sustainable wireless communications. However, the inherent variability and intermittency of solar energy, coupled with precise intercell interference management, significantly hinder efficient network operation. To resolve these challenges, we propose a multiagent distributed deep Q-network framework, where the distributed base stations learn the optimal transmit power control policies. To further enhance adaptability under varying solar conditions, we present a daily model transfer with a fine-tuning approach, enabling efficient deployment without extensive training overhead. Simulation results demonstrate that the proposed methods remarkably improve energy efficiency while maintaining robust adaptability under dynamic solar conditions, revealing their potential for sustainable small-cell network deployments.

In this study, we consider a space-time line code (STLC) system with N transmit antennas and two receive antennas. Although the STLC system is scalable to an arbitrary number of transmit antennas, a large number of them will increase the hardware cost and complicate the implementation of the system. To resolve this practical limitation, we propose a transmit antenna selection (TAS) scheme for the N-by-2 STLC system. If S ≤ N antennas are used for the transmission, the STLC transmitter selects the S antennas such that the instantaneous signal-to-noise ratio (SNR) is maximized. For a comprehensive performance analysis, the instantaneous SNR of the proposed TAS is characterized in terms of the statistical mean and moment-generating function (MGF). To investigate the performance of the proposed TAS approach, the approximated expression of error rate is derived based on the MGF method. Moreover, using asymptotic analysis, we show that the proposed TAS-STLC system achieves full spatial diversity of 2N, while the coding gain is affected by N, S, and the modulation order. As a special case, we also provide a mathematical analysis of the error rate of the conventional STLC system when N = S.

In this paper, we propose a CRC-aided soft-output (CASO) detection for uplink multi-user multiple-input multiple-output systems with one-bit ADCs to improve the error rate while maintaining low latency. After CRC checking, the CASO detection constructs a refined subcode of a spatial-domain code by exploiting successfully decoded messages from the previous iteration. Based on the refined subcode, more reliable soft messages can be extracted to utilize in the rest decoding process. Since multiple messages can be successfully canceled with the aid of CRC checking, the CASO detection can prevent error propagation and suppress increment of latency. Simulation results demonstrate that the CASO detection can provide improved error rate compared to the conventional detections though increment of latency is insignificant for high SNR.

Length-compatible polar codes are a class of polar codes which can support a wide range of lengths with a single pair of encoder and decoder. In this paper we propose a method to construct length-compatible polar codes by employing the reduction of the 2n× 2npolarizing matrix proposed by Arikan. The conditions under which a reduced matrix becomes a polarizing matrix supporting a polar code of a given length are first analyzed. Based on these conditions, length-compatible polar codes are constructed in a suboptimal way by codeword-puncturing and information-refreezing processes. They have low encoding and decoding complexity since they can be encoded and decoded in a similar way as a polar code of length 2n. Numerical results show that length-compatible polar codes designed by the proposed method provide a performance gain of about 1.0 - 5.0 dB over those obtained by random puncturing when successive cancellation decoding is employed.

A blind algorithm is proposed in order to compensate for the phase noise resulting from imperfect oscillators in orthogonal frequency-division multiplexing (OFDM) systems over constant modulus modulation. In the proposed algorithm, one received OFDM symbol is partitioned into subblocks in the time domain and the phase noise over each subblock is approximated as its time-average. Under the approximation, the squared magnitude of the channel gain multiplied by the data symbol at each subcarrier is shown to be expressed in terms of these time-averages and the discrete Fourier transform (DFT) coefficients of the received samples at each subblock with zero padding. Based on the relation, the proposed algorithm compensates for the phase noise without pilot symbols. Numerical results show that the proposed algorithm outperforms conventional algorithms as well as it requires lower computational complexity.