This paper provides a comprehensive performance analysis of the reconfigurable intelligent surfaces (RIS)-assisted receive generalized space-shift keying (RGSSK) and the RIS-assisted receive generalized spatial modulation (RIS-RGSM) schemes. Specifically, we derive closed-form expressions for the pairwise error probabilities (PEPs) of the RIS-RGSSK and RIS-RGSM schemes when two antennas are activated at the receiver. Our analytical derivations eliminate the need for numerical approximations or complex integration methods. Finally, we verify our analytical results via simulations, demonstrating the accuracy of our expressions.

This paper investigates sum-rate maximization for reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) networks, while ensuring that the energy constraints of the wireless nodes are satisfied. The formulated problem involves the joint optimization of the phase-shifts of the RIS reflecting elements (passive beamforming) and the transmit power control for each transmitter. Given the highly non-convex nature of this optimization problem, obtaining its global optimal solution is non-trivial. To this end, we propose a new algorithm that leverages fractional programming and penalty dual decomposition techniques to obtain a high-quality sub-optimal solution. Our numerical results highlight the superiority of the proposed algorithm, as it consistently achieves substantially higher sumrates in comparison to the benchmark schemes.

With the massive deployment of Internet of Things (IoT) devices in sixth-generation networks, several critical challenges have emerged, such as large communication overhead, coverage limitations, and limited battery lifespan due to high energy consumption. Federated learning (FL), wireless power transfer (WPT), multi-antenna access point (AP), and reconfigurable intelligent surfaces (RIS) can mitigate these challenges by reducing the need for large data transmissions, enabling sustainable energy harvesting, and optimizing the propagation environment. Compared to conventional RIS, simultaneously transmitting and reflecting (STAR)-RIS not only extends coverage from half-space to full-space but also improves energy saving through appropriate mode selection. Motivated by the need for sustainable, low-latency, and energy-efficient communication in large-scale IoT networks, this paper investigates the efficient STAR-RIS mode in the uplink and downlink phases of a WPT-FL multi-antenna AP network with non-orthogonal multiple access to minimize energy consumption, a joint optimization that remains largely unexplored in existing works on RIS or STAR-RIS. We formulate a non-convex energy minimization problem for different STAR-RIS modes, i.e., energy splitting (ES) and time switching (TS), in both uplink and downlink transmission phases, where STAR-RIS phase shift vectors, beamforming matrices, time and power for harvesting, uplink transmission, and downlink transmission, local processing time, and computation frequency for each user are jointly optimized. To tackle the non-convexity, the problem is decoupled into two subproblems: the first subproblem optimizes STAR-RIS phase shift vectors and beamforming matrices across all WPT-FL phases using block coordinate descent over either semi-definite programming or Rayleigh quotient problems, while the second one allocates time, power, and computation frequency via the one-dimensional search algorithms or the bisection algorithm. Simulation results demonstrate that TS STAR-RIS in both uplink and downlink transmissions achieves the lowest energy consumption, outperforming ES and conventional RIS schemes due to its flexible phase shift adaptation and lower interference levels.

LoRa, a low-power long-range physical-layer communication method, is one of the emerging technologies in low-power wide-area networks (LPWANs). In LoRa, a linearly varying-frequency up chirp and its cyclic shifts act as an orthonormal basis set for message representation. The number of orthonormal basis functions dictates the achievable bit rate of a LoRa system. This article aims to increase the achievable data rate of a conventional LoRa system by adding a set of new orthonormal basis functions to the existing set. Specifically, we use a linearly varying-frequency down chirp and its cyclic shifts to generate the second set of orthonormal basis functions in the proposed scheme, named slope-shift-keying LoRa (SSK-LoRa) modulation. We also develop both low-complexity optimum coherent and noncoherent detection algorithms for the proposed SSK-LoRa modulation. We then obtain closed-form analytical and tight approximations for the bit and symbol error probabilities of noncoherent detection in a Rayleigh fading environment. Our proposed SSK-LoRa scheme is shown to outperform the state-of-the-art LoRa-based modulation schemes.

This article introduces a novel frequency-shift chirp spread spectrum (FSCSS) system with index modulation (IM). By using combinations of orthogonal chirp signals for message representation, the proposed FSCSS with index modulation (FSCSS-IM) system is very flexible to design and can achieve much higher data rates than the conventional FSCSS system under the same bandwidth. The article presents optimal detection algorithms, both coherently and noncoherently, for the proposed FSCSS-IM system. Furthermore, a low-complexity noncoherent detection algorithm is also developed to reduce the computational complexity of the receiver, which is shown to achieve near-optimal performance. The results are presented to demonstrate that the proposed system, while enabling much higher data rates, enjoys similar bit-error performance as that of the conventional FSCSS system.

Non-binary kernels are used to improve the length flexibility of polar codes. Given the long decoding latency of the successive-cancellation (SC) decoder, devising fast decoding solutions for non-binary kernels is necessary. In this work, we identify a new node in the decoding tree of polar codes which are constructed by commonly used ternary kernels. We call this t-dimensional SPC (tD-SPC) node and propose a low-complexity decoder for it. Moreover, we adapt a node introduced for binary kernel to be used in the fast SC decoding of the 3×3 kernel polar codes. Simulation results show that implementing the proposed fast decoders can reduce the decoding latency by more than 40% if a performance loss of just 0.5 dB is tolerated.

This paper generalizes the conventional noncoherent OFDM-IM systems by allowing selection of different numbers of active subcarriers for message representation. We then present the maximum-likelihood (ML) detection rule for frequency-selective block fading channels. The performance of the ML receiver is analyzed in terms of pairwise-error probability as well as diversity order. Asymptotic analysis of the proposed system reveals the role of partial Hamming distance in designing diversity-exploiting activation patterns. Practical issues including low-complexity receiver, and code (activation pattern) design techniques are discussed. Furthermore, the effect of inter-carrier interference in fast fading scenarios, and generalization of the technique to multiple-antenna scenarios are studied. Finally, we present simulation results to illustrate performance benefits of the generalized OFDM-IM systems over the conventional noncoherent OFDM-IM systems.

The successive-cancellation list (SCL) and successive-cancellation flip (SCF) decoding can be used to improve the performance of polar codes, especially for short to moderate length codes. However, their serial decoding nature results in significant decoding latencies. Implementing some operations in parallel can reduce their decoding latencies. This paper presents fast implementations of the SCL and SCF decoders. In particular, we propose fast parallel list decoders for five newly identified types of nodes in the decoding tree of a polar code, which significantly improves the decoding latency. We also present novel fast SCF decoders that decode some special nodes in the decoding tree of a polar code without serially computing bit log-likelihood ratios. Using our proposed fast parallel SCF decoders, we observed an improvement up to 81% with respect to the original SCF decoder. This significant reduction in the decoding latency is observed without sacrificing the bit-error-rate performance of the code.

This paper proposes a novel lower bound on the Bhattacharyya parameter of synthesized channels in polar codes. The proposed bound is a result of a newly defined merge operation that reduces the cardinality of output alphabets of a symmetric binary-input discrete memoryless channel. By repeated applications of the proposed merge operation, we establish a universal bound on the Bhattacharyya parameters of synthesized channels that holds for any symmetric binary-input discrete memoryless transmission channel. We then discuss some applications of the new bound. For example, using the derived universal lower bound along with the existing upper bound, we find a partial order among the Bhattacharyya parameters of those synthesized channels that cannot be ordered through existing results. This ordering can help efficient design of polar codes. In addition, some extremal behaviors of the binary-symmetric channel are also proved.

Massive multiple‐input multiple‐output (MIMO) systems bring manifold improvements in the system spectral efficiency but result in high hardware and processing complexity at the base station. Employing hybrid precoding at the base station can reduce such complexity. In this study, unlike most existing work on hybrid precoding design, the authors consider a sub‐connected analogue combining structure to reduce the complexity. Starting from an important observation on the effect of sequentially designed analogue phased arrays on users' sum rate, the authors develop three low‐complexity hybrid precoding schemes for a multi‐user massive MIMO system. The proposed schemes apply equal gain transmission (EGT) based analogue beamforming to reap the diversity benefit of an analogue phased array and employ zero‐forcing (ZF) beamforming for nullifying inter‐user interference. The authors carry out an extensive computational complexity analysis and simulation study on the proposed schemes. The proposed singular‐value decomposition based EGT scheme outperforms all others but incurs the highest computational burden. On the other hand, the sequential‐EGT scheme is the least computationally intensive scheme but shows the worse performance amongst them.

The high hardware cost associated with multiple antennas at the secondary transmitter of an underlay cognitive radio (CR) can be reduced by antenna selection. This paper analyzes different power adaptive transmit antenna selection (TAS) schemes for an underlay CR, which ensure that the instantaneous interference caused by the secondary transmitter to the primary receiver is below a predetermined level. We consider the optimal continuous power adaptive TAS and present a low-complexity antenna and power level selection scheme, named sequential antenna and power level selection scheme (SAPS), for discrete power adaptation. Exact statistical characterizations of the signal-to-interference plus noise ratio at the secondary receiver are derived for the considered schemes. Based on the newly derived statistics, we prove that the considered schemes achieve the highest diversity order equaling the number of antennas at the secondary transmitter. Further, we also derive a closed-form expression of the ergodic capacity for the underlay CR with SAPS scheme. Finally, we show that the proposed scheme outperforms existing schemes in terms of ergodic capacity.

We present a transmit antenna subset selection scheme for an underlay cognitive system serving multiple secondary receivers. The secondary system employs zero-forcing beamforming to nullify the interference to multiple primary users and eliminate inter-user interference to the secondary users simultaneously. Simulation results show that the proposed scheme achieves near-optimal performance with low computational complexity. Lastly, an optimal power allocation strategy is also introduced to improve the secondary network throughput.

Cognitive radio (CR) technology addresses the problem of spectrum under-utilization. In underlay CR mode, the secondary users are allowed to communicate provided that their transmission is not detrimental to primary user communication. Transmit antenna selection is one of the low-complexity methods to increase the capacity of wireless communication systems. In this article, we propose and analyze the performance benefit of a transmit antenna selection scheme for underlay secondary system that ensures the instantaneous interference caused by the secondary transmitter to the primary receiver is below a predetermined level. Closed-form expressions of the secondary link outage probability, higher order amount of fading, and ergodic capacity are derived for the proposed scheme. Monte-carlo simulations are also carried out to confirm various mathematical results presented in this article.

Receive antenna selection is a low complexity scheme to reap diversity benefits. We analyze the performance of a receive antenna selection scheme in spectrum sharing systems where the antenna that results in highest signal-to-interference plus noise ratio at the secondary receiver is selected to improve the performance of secondary transmission. Exact and asymptotic behaviours of the received SINR are derived for both general and interference limited scenarios over general fading environment. These results are then applied to the outage and average bit error rate analysis when the secondary transmitter changes the transmit power in finite discrete levels to satisfy the instantaneous interference constraint at the primary receiver.