The impact of both multiplicative and additive hardware impairments (HWIs) on multiple-input multiple-output affine frequency division multiplexing (MIMO-AFDM) systems is investigated. For small-scale MIMO-AFDM systems, a tight bit error rate (BER) upper bound associated with the maximum likelihood (ML) detector is derived. By contrast, for large-scale systems, a closed-form BER approximation associated with the linear minimum mean squared error (LMMSE) detector is presented, including realistic imperfect channel estimation scenarios. Our first key observation is that the full diversity order of a hardware-impaired AFDM system remains unaffected, which is a unique advantage. Furthermore, our analysis shows that 1) the BER results derived accurately predict the simulated ML performance in moderate-to-high signal-to-noise ratios (SNRs), while the theoretical BER curve of the LMMSE detector closely matches that of the Monte-Carlo based one. 2) MIMO-AFDM is more resilient to multiplicative distortions, such as phase noise and carrier frequency offset, compared to its orthogonal frequency division multiplexing (OFDM) counterparts. This is attributed to its inherent chirp signal characteristics; 3) MIMO-AFDM consistently achieves superior BER performance compared to conventional MIMO-OFDM systems under the same additive HWI conditions, as well as different velocity values. The latter is because MIMO-AFDM is also resilient to the additional inter-carrier interference (ICI) imposed by the nonlinear distortions of additive HWIs. In a nutshell, compared to OFDM, AFDM demonstrates stronger ICI resilience and achieves the maximum full diversity attainable gain even under HWIs, thanks to its intrinsic chirp signalling structure as well as to the beneficial spreading effect of the discrete affine Fourier transform.

Dynamic metasurface antennas (DMAs) are promising alternatives to fully digital (FD) architectures, enabling hybrid beamforming via low-cost reconfigurable metasurfaces. In DMAs, holographic beamforming is achieved through tunable elements by Lorentzian-constrained holography (LCH), significantly reducing the need for radio-frequency (RF) chains and analog circuitry. However, the Lorentzian constraints and limited RF chains introduce a trade-off between reduced system complexity and beamforming performance, especially in dense network scenarios. This paper addresses resource allocation in multi-user multiple-input-single-output (MISO) networks under the Signal-to-Interference-plus-Noise Ratio (SINR) constraints, aiming to minimize total transmit power. We propose a holographic beamforming algorithm based on the Generalized Method of Lorentzian-Constrained Holography (GMLCH), which optimizes DMA weights, yielding flexibility for using various LCH techniques to tackle the aforementioned trade-offs. Building upon GMLCH, we further propose a new algorithm i.e., Adaptive Radius Lorentzian Constrained Holography (ARLCH), which achieves optimization of DMA weights with additional degree of freedom in a greater optimization space, and provides lower transmitted power, while improving scalability for higher number of users. Numerical results show that ARLCH reduces power consumption by over 20% compared to benchmarks, with increasing effectiveness as the number of users grows.

Generalized spatial modulation-aided affine frequency division multiplexing (GSM-AFDM) is conceived for reliable multiple-input multiple-output (MIMO) communications over doubly selective channels. We commence by proposing several low-complexity detectors for large-scale GSM-AFDM systems to meet the diverse requirements of heterogeneous receiver designs in terms of detection complexity and reliability. Specifically, we introduce the linear minimum mean square error (LMMSE) equalizer-based maximum likelihood detector (LMMSE-MLD). By exploiting the GSM properties, we then derive the LMMSE-based transmit-antenna activation pattern (TAP) check-based log-likelihood ratio detector (LMMSE-TC-LLRD). In addition, we propose a pair of new detectors, namely the greedy residual check detector (GRCD) and the reduced space check detector (RSCD). We also derive a bit error rate (BER) upper-bound by considering the MLD. Our analytical results are also available for multiple-input multiple-output (MIMO)-AFDM, since MIMO-AFDM can be regarded as a special case of the proposed GSM-AFDM. Our simulation results demonstrate that 1) the BER upper bound derived is tight for moderate to high signal-to-noise ratios (SNRs), 2) the proposed GSM-AFDM achieves lower BER than its conventional orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS) and AFDM counterparts. Specifically, at a BER of 10−4and a velocity of 540 km/h, the proposed GSM-AFDM is capable of attaining about 6 dB SNR gain compared to GSM-OFDM, and 3) the conceived detectors strike a compelling trade-off between the BER and complexity.

This paper proposes a novel non-orthogonal affine frequency division multiplexing (nAFDM) waveform for reliable high-mobility communications with enhanced spectral efficiency (SE). The key idea is to introduce a bandwidth compression factor into the AFDM modulator to enable controllable subcarrier overlapping. We first detail the proposed nAFDM transceiver and derive the corresponding input-output signal relationship. Then, an efficient nAFDM signal generation method based on the inverse discrete Fourier transform (IDFT) is proposed, enabling practical implementation using existing inverse fast Fourier transform (IFFT) modules without additional hardware complexity. Next, to characterize the impact of non-orthogonal modulation, we derive a closed-form expression of inter-carrier interference (ICI), showing its dependence on the bandwidth compression factor. To mitigate the resulting interference, we propose a soft iterative detection algorithm and a low-complexity implementation approach that leverages the distribution characteristics of ICI. Simulation results demonstrate that 1) in terms of bit error rate (BER), the proposed nAFDM can achieve nearly identical BER compared to conventional AFDM, while outperforms other waveform counterparts; 2) nAFDM is capable of striking higher SE compared to other existing waveforms; and 3) the proposed nAFDM achieves an attractive BER vs. SE trade-off, and the proposed soft iterative detection (ID) scheme can attain a trade-off between BER and complexity.

In this paper, we utilize a downlink hybrid Non-Orthogonal Multiple Access (NOMA) framework to support multiple semantic and bit users within the communication network. The hybrid NOMA setup exploits both NOMA and Orthogonal Multiple Access (OMA) which has the benefit of enhancing Spectral Efficiency (SE) by allowing users to dynamically access the resources in multiple heterogeneous slots. This enables integrating semantic and bit users based on their channel gains, while adopting bit-to-semantic decoding order in slots including heterogeneous users. This allows bit user to first decode its signal by treating the semantic signal as interference and subsequently semantic signal is decoded without interference. Semantic users are modeled using a deep learning-based system equipped with pre-trained neural networks. An optimization problem for the power allocation is formulated with the aim of maximizing the equivalent ergodic semantic SE with a constraint on the total available power of the Access Point (AP). The proposed algorithm uses NOMA in shared slots and OMA in bit-user-only slots. Simulation results validate the benefits of heterogeneous users hybrid NOMA setup in comparison to OMA-only for heterogeneous users.

This paper investigates the average achievable rate of reconfigurable intelligent surface (RIS) assisted point-to-point short-packet communication with multiple-antenna reception. First, using a random matrix theory based approach, closed-form upper bounds for the system’s average achievable rate are obtained for two asymptotic regimes: high and low transmit powers. Detailed performance analysis and insights based on the rate metric are provided. Then, a metric for quantifying the potential deterministic behavior of the system’s channels, specifically in the short-packet regime under consideration, is proposed. The hardening is studied, and key insights are provided, including the impact of the finite blocklength on the average achievable rate of the system, particularly for small numbers of receive antennas and in the high transmit power regime. The practical application of the hardening metric from a system design viewpoint is also discussed.

This paper proposes a spectrum-efficient non-orthogonal affine frequency division multiplexing (AFDM) waveform for reliable high-mobility communications in the upcoming sixth-generation (6G) mobile systems. Our core idea is to introduce a compression factor to enable controllable subcarrier overlapping in chirp-based AFDM modulation. To mitigate inter-carrier interference (ICI), we introduce linear precoding at the transmitter and an iterative detection scheme at the receiver. Simulation results demonstrate that these techniques can effectively reduce interference and maintain robust bit error rate (BER) performance even under aggressive compression factors and high-mobility channel conditions. The proposed non-orthogonal AFDM waveform offers a promising solution for next-generation wireless networks, balancing spectrum efficiency and Doppler resilience in highly dynamic environments.

In this paper, we present a deep reinforcement learning (DRL) framework for vehicular optical camera communication (OCC) systems that ensures ultra-reliable and low-latency communication (uRLLC). We first formulate a throughput maximization problem that aims at optimizing speed of vehicles, channel code rate, and modulation order while respecting the uRLLC requirements. We model reliability by satisfying a target bit error rate and latency as transmission latency. To improve the transmission rate and provide high reliability and low latency, our scheme uses low-density parity-check codes and adaptive modulation. We then solve the optimization problem using the actor-critic-based DRL scheme with Wolpertinger framework. We employ a deep deterministic policy gradient algorithm to operate over continuous action spaces. The evaluation confirms that our proposed DRL-based optimization scheme achieves superior performance compared to radio frequency-based communication systems as well as variants of the proposed scheme. Finally, we verify through simulations that our proposed solution can maximize the communication rate while meeting the uRLLC constraints.

In this paper, we focus on investigating the link-layer rate within a non-orthogonal multiple access (NOMA) system operating in the finite blocklength (FBL) regime, specifically designed for short-packet communications. By leveraging the effective capacity (EC) framework, latency and reliability in FBL, encompassing parameters such as the block error probability and the delay outage probability, are analyzed for two scenarios, namely, system operation with multiple NOMA pairs and the two-user NOMA operation. Closed-form expressions for the EC in the two cases are derived by assuming that transmissions are subject to Rayleigh fading and adopting a practical path-loss model. Numerical results are provided to validate the analytical findings, and to highlight the impact of the transmit signal-to-noise ratio, the blocklength, the delay exponent, and the block error probability, on the EC and the delay outage probability. Furthermore, various pairing configurations are investigated and demonstrate that the paired NOMA set attains the highest total EC for users experiencing substantial differences in their channel conditions.

In this work, we study the use of non-orthogonal multiple access (NOMA) and orthogonal time frequency space (OTFS) modulation in a multiple-input multiple-output (MIMO) communication network where mobile users (MUs) with different mobility profiles are grouped into clusters. We consider a downlink scenario where a base station (BS) communicates with multiple users that have diverse mobility profiles. High-mobility (HM) users' signals are placed in the delay-Doppler (DD) domain using OTFS modulation in order to transform their time-varying channel into a sparse static channel, while low-mobility (LM) users signals are placed in the time-frequency (TF) domain. Precoding is adopted at the BS to direct focused beams towards each cluster of users. Moreover, NOMA spectrum sharing is used in each cluster to allow the coexistence of a single HM user and multiple LM users within the same resource block. LM users access disjoint subchannels to ensure their orthogonality. All users within the same cluster first detect the HM user's signal. Afterward, LM users suppress the interference from the HM user and detect their own signals. Closed-form expressions of the detection signal-to-noise ratios (SNRs) are derived. The numerical results showed that the performance of the proposed system highly depends on the number of LM users, the number of clusters and the power allocation factors between HM and LM users.

In dynamic and time-varying vehicular networks, existing vehicular communication systems cannot guarantee ultra-reliable and low latency communication (uRLLC). To address this, we propose a novel deep reinforcement learning-based vehicular optical camera communication (OCC) system with an aim to maximize the throughput and ensure uRLLC. To achieve this, our scheme chooses the optimal code rate, modulation scheme and speed of vehicles for multiple vehicular links. We use OCC, which offers interference-free communication as an alternative to radio frequency systems. Moreover, we employ 5G New Radio low-density parity-check codes and an adaptive modulation scheme to support variable rates and ultra-reliability. The proposed large-scale and continuous problem is solved through an actor-critic algorithm based on Wolpertinger architecture. We extendedly evaluate the system performance and compare it with several other schemes from the literature as well as with variants of our scheme. We observe from the results that the proposed method achieves higher average throughput and lower latency than all the other schemes under comparison. Further, the proposed scheme can meet the uRLLC constraints, whereas other schemes under comparison fail to respect these constraints most of the time.

In this paper, we propose a vehicular optical camera communication system that can meet low bit error rate (BER) and ultra-low latency constraints. First, we formulate a sum spectral efficiency optimization problem that aims at finding the speed of vehicles and the modulation order that maximizes the sum spectral efficiency subject to reliability and latency constraints. This problem is mixed-integer programming with nonlinear constraints, and even for a small set of modulation orders, is NP-hard. To overcome the entailed high computational and time complexity which prevents its solution with traditional methods, we first model the optimization problem as a partially observable Markov decision process. We then solve it using an independent Q-learning framework, where each vehicle acts as an independent agent. Since the state-action space is large we then adopt deep reinforcement learning (DRL) to solve it efficiently. As the problem is constrained, we employ the Lagrange relaxation approach prior to solving it using the DRL framework. Simulation results demonstrate that the proposed DRL-based optimization scheme can effectively learn how to maximize the sum spectral efficiency while satisfying the BER and ultra-low latency constraints. The evaluation further shows that our scheme can achieve superior performance compared to radio frequency-based vehicular communication systems and other vehicular OCC variants of our scheme.

Physical-layer Network Coding (PNC) has great potential to improve the throughput and latency in wireless networks. However, there are two main challenges in PNC systems that do not exist in the conventional Point-to-Point$(\mathrm{P}2\mathrm{P})$communication systems: 1) time and frequency asynchrony of the paired PNC users; and 2) ambiguity of the PNC mapping at the relay node. To address these challenges, in this paper, we apply precoding for power control and phase synchronization of the paired PNC users, while we use modulo$-\sqrt{M}$addition for the PNC mapping ambiguity removal in higher-order M-ary Quadrature Amplitude Modulations (M-QAM). We evaluate the performance of the system in the framework of the Orthogonal Frequency Division Multiplexing (OFDM)-PNC systems with cyclic prefix extension under Rayleigh faded Tapped Delay Line (TDL)-C and Rician faded TDL-D channel models, proposed by the Third Generation Partnership Project$(3\text{GPP})$, as well as the Additive White Gaussian Noise (AWGN) channel model. The results reveal that our proposed technique can achieve a significant Signal-to-Noise Ratio (SNR) improvement of 12$\text{dB}$over its asynchronous OFDM-PNC counterpart (without precoding) for Binary Phase Shift Modulation (BPSK) under a TDL-C faded channel model. Moreover, without channel coding, our proposed PNC technique requires an SNR of around$13\text{dB}$to deliver a two-way 16-QAM communication at a Bit Error Rate of 10−3under a Rayleigh faded TDL-C channel.

Millimetre wave (mmWave) communication is a promising technology which can fulfil the growing demands for spectrum for future wireless networks. One of the key areas for the development of the mmWave networks is the Internet of Things (IoT) communications within fifth generation (5G) and beyond 5G networks. For significant analysis and development of the compliant IoT systems through testbed implementation, current mmWave spectrum transceivers are too expensive when substantial number of the nodes is required by the IoT applications. Considering all the above, it is suggested to use Software Defined Radio (SDR) transceivers with a lower frequency band and with an increased distance between the nodes. The idea is to scale observation time and distance to emulate mmWave radio without actual mmWave hardware. Using scaling factors for the certain system parameters to keep the signal characteristics in accordance with the mmWave band makes it possible. This approach allows to develop mmWave IoT testbeds with significant improvement in the system scalability and cost-effectiveness without the need to transmit and receive the signal in the mmWave band. In this paper, the concept of SDR-based Hardware-in-the-loop (HIL) system combined with the observation time and distance scaling approach is proposed. As an example, a testbed with a simple Wireless Physical Network Coding scheme is implemented and demonstrated.

Achieving ultra-reliable and low latency communication (uRLLC) in vehicular networks is challenging because of their time-varying and dynamic nature. In this paper, we propose a deep reinforcement learning (DRL) based vehicular optical camera communications (OCC) system that aims at maximizing the transmission rate. In doing so, we optimize the speed of vehicles, the channel code rate, and the modulation order while respecting the uRLLC requirements. We define reliability by satisfying a predefined bit error rate and latency as transmission latency. To improve the transmission rate and ensure reliability and low latency, we use low-density parity-check codes and adaptive modulation. We then solve the optimization problem using the actor-critic DRL framework with Wolpertinger architecture. We deal with the continuous action spaces by employing a deep deterministic policy gradient algorithm. The evaluation verifies that our proposed optimization scheme can achieve superior performance than the comparison schemes. Finally, the results further confirm that the proposed solution can maximize the communication rate while guaranteeing the uRLLC requirements.

In this paper, we study the secrecy performance of short packet secure communications over a fading wiretap channel when there are multiple receivers and eavesdroppers. In particular, we evaluate and compare the performance of colluding and non-colluding eavesdropping modes, in terms of achievable secrecy throughput. Our aim is to determine whether eavesdroppers' collusion degrades the average secrecy throughput compared to a non-colluding scenario. After deriving closed-form approximations on average secrecy throughput for both scenarios, Monte-Carlo simulations are performed to obtain the accuracy of each approximation. Our results reveal that the impact of colluding eavesdroppers on the average secrecy throughput causes more loss than a non-colluding case, especially with the increasing number. Besides, an increased number of receivers does not eliminate the negative impact of eavesdroppers.

This paper investigates the performance of point-to-point communications in which the source node is capable of harvesting and storing energy from radio-frequency (RF) signals, and then using the harvested energy to communicate with its end destination. This operation is executed via a time-switching protocol at the source node while considering that the energy spent from its battery is fixed within a communication time interval. A mathematical framework is developed for the performance evaluation of the communication system subject to constraints on the allowable energy outage. A virtual energy queuing model is proposed and used to satisfy the assumptions of the large deviation principle, which is then used for the performance analysis. Considering all channels to be subject to Rayleigh fading, closed-form expressions are obtained for the energy used from the transmitter's battery and for the energy-outage probability of the system. Numerical results are also provided, and the effects of various parameters, including those of the time-switching protocol, the harvested energy, the distance between nodes, and the transmit power, on the performance of the RF energy-harvesting based communication systems are investigated.

Optical camera communications (OCC) has emerged as a key enabling technology for the seamless operation of future autonomous vehicles. In this paper, we introduce a spectral efficiency optimization approach in vehicular OCC. Specifically, we aim at optimally adapting the modulation order and the relative speed while respecting bit error rate and latency constraints. As the optimization problem is NP-hard problem, we model the optimization problem as a Markov decision process (MDP) to enable the use of solutions that can be applied online. We then relaxed the constrained problem by employing Lagrange relaxation approach before solving it by multi-agent deep reinforcement learning (DRL). We verify the performance of our proposed scheme through extensive simulations and compare it with various variants of our approach and a random method. The evaluation shows that our system achieves significantly higher sum spectral efficiency compared to schemes under comparison.

Nonorthogonal multiple access (NOMA)-based multiple-input-multiple-output (MIMO), which has the potential to provide both massive connectivity and high spectrum efficiency, is considered as one of the efficient techniques for sixth-generation (6G) wireless systems. In massive Internet of Things (IoT) networks, the user-set selection is crucial for enhancing the overall performance of NOMA-based systems when compared with orthogonal multiple access (OMA) techniques. In this article, we propose a user-set selection algorithm for IoT uplink transmission to improve the sum data rate of the NOMA-based MIMO systems. In order to exchange data between the selected IoT pairs, we propose to employ wireless physical-layer network coding (PNC) to further improve the spectral efficiency and reduce the delay to fulfill the requirements of future IoT applications. Performance evaluations are provided based on both the sum data rate and bit error rate for the proposed NOMA-based MIMO with PNC in the considered massive IoT scenarios.

This paper studies the performance of short packet communications in the presence of multiple eavesdroppers. We start our investigation by examining the fading wiretap channel, where the communication is overheard by multiple non-colluding single antenna eavesdroppers. A closed-form expression for the average secrecy throughput is derived, when the transmitter has a single antenna. The Monte-Carlo simulations show a close match of the analytical expression with the numerical results. Moreover, the optimal blocklength value that maximizes the secrecy throughput is determined, when the communication is observed by single and multiple eavesdroppers. We then extend our analysis for the case of a multiple-antenna transmitter and consider artificial noise (AN) to confuse the eavesdroppers. A closed-form expression for the average secrecy throughput is obtained for the scenario of a two-antenna transmitter and two eavesdroppers with a single antenna. The results demonstrate the validity of the approximation when compared with Monte-Carlo simulations. The results further reveal that an increased number of antennas at the transmitter is associated with higher average secrecy throughput and applying AN helps to eliminate the harm of the eavesdroppers.

In this paper, we study joint adaptive M-QAM modulation and power adaptation for a downlink two-user non-orthogonal multiple access (NOMA) network. Without sacrificing bit error rate (BER), joint adaptive transmission can fully utilize the time-varying nature of wireless channels, by allowing both power and rate to adapt to channel fading. Two adaptive power allocation strategies, namely,Scheme 1andScheme 2, each of which guarantees the minimum target rate for one user while supporting the highest possible rate for the other, are first proposed. Then, based on the two power schemes, the performance of joint adaptive transmission in terms of average spectral efficiency (SE) is studied for continuous-rate and discrete-rate modulation, while guaranteeing the minimum required rate and BER requirements. With the focus on practical discrete-rate M-QAM modulation, it is proved that for the strong user inScheme 1and the weak user inScheme 2, their average SEs converge to the minimum target rates. In order to further increase the total transmission rate, we then propose a dynamic rate and power adaptation (DRPA) algorithm, aiming to increase the rate of one user without sacrificing the rate of the other. It is shown that at high SNRs, the DRPA algorithm allows the strong user inScheme 1and the weak user inScheme 2to continue to increase their transmission rates until reaching the highest modulation order that the system can support. Hence, the total transmission rate can be greatly increased at high SNRs due to the adoption of DRPA, by allowing both users in each scheme to reach the highest transmission rate in the system.

In this paper, we study the total effective capacity (EC) of single-cluster non-orthogonal multiple access (NOMA) networks and demonstrate the performance gain of single-cluster NOMA over user-paired NOMA and orthogonal multiple access (OMA). Specifically, the exact closed-form expression and an approximate closed-form expression at high signal-to-noise ratios (SNRs), in terms of the total EC, are derived for single-cluster NOMA networks. The derivations reveal that the total EC at high SNRs only relies on the statistical delay requirement of the strongest user and is independent of the other users' delay requirements. Further, we theoretically analyze the total EC differences between single-cluster NOMA and user-paired NOMA/OMA communications and explore the impact of transmit SNR. Simulation results verify the accuracy of analytical results and further reveal that the single-cluster NOMA network achieves a greater gain in terms of the total EC, compared to the conventional OMA, when the number of users increases.

In vehicular ad hoc networks, autonomous vehicles generate a large amount of data prior to support in-vehicle applications. So, big storage and high computation platform are needed. On the other hand, the computation for vehicular networks at the cloud platform requires low latency. Applying edge computation (EC) as a new computing paradigm has potentials to provide computation services while reducing the latency and improving the total utility. We propose a three-tier EC framework to set the elastic calculating processing capacity and dynamic route calculation to suitable edge servers for real-time vehicle monitoring. This framework includes the cloud computation layer, EC layer, and device layer. The formulation of the resource allocation approach is similar to an optimization problem. We design a new reinforcement learning (RL) algorithm to deal with the resource allocation problem assisted by cloud computation. By integration of EC and software-defined networking (SDN), this study provides a new SDN edge (SDNE) framework for resource assignment in vehicular networks. The novelty of this work is to design a multiagent RL-based approach using experience reply. The proposed algorithm stores the users' communication information and the network tracks' state in real time. The results of simulation with various system factors are presented to display the efficiency of the suggested framework. We present results with a real-world case study.

In this article, we investigate the resilience of Massive MIMO Physical Layer Network Coding (PNC) to jamming attack in both sub-6 GHz and millimeter-Wave (mmWave) systems in vehicular networks. Massive MIMO generally is resilient to jamming attacks, and we investigate the impact that PNC has on this resilience, if combined with Massive MIMO. The combination of Massive MIMO and PNC has shown a significant improvement in the bit error rate (BER) in our previous investigation. The corresponding framework is analysed against a barraging attack from a jammer, where the jamming channel is not known to the base station (BS), and the jammer can use any number of transmit antennas. Over Rayleigh channel, our simulation results reveal that Massive MIMO PNC performs better in the lower signal-to-noise ratio (SNR) regions to jamming attacks and this is achieved at twice the spectral efficiency. A similar performance is observed over mmWave channel.

In this paper, non-orthogonal multiple access (NOMA) in cooperative relay system is considered, where a source node communicates with a pair of energy harvesting (EH) user equipments through a multiple antennas relay node. A hybrid protocol is adopted at the relay, in which if the relay can successfully decode the signals, decode-and-forward (DF) protocol will be adopted to forward the signals to the users. Otherwise, amplify-and-forward (AF) protocol will be implemented. Assuming that the users adopt maximal ratio combining (MRC) to combine the received signals in the two cooperative phases, new explicit analytical expressions for the average sum-rate are derived when the relay works in, 1) AF mode, and 2) DF mode, in two scenarios when one user is the stronger in both cooperation phases, and when an alternative user is stronger in each phase. Then, the investigation is extended to the case where the relay is an untrusted node, and cooperative jamming technique is proposed to degrade the ability of the relay to decode the signals and enforce the relay to operate always in AF mode. For the untrusted relay scenario, new analytical expression for the average secrecy rate is derived. Monte Carlo simulations are provided to validate the analysis. The simulation results reveal that the location of the relay is the key parameter to achieve the best performance.

In the fifth generation and beyond (B5G), delay constraints emerge as a topic of particular interest, e.g. for ultra-reliable low latency communications (URLLC) such as autonomous vehicles and enhanced reality. In this paper, we study the performance of a two-user uplink NOMA network under statistical quality of service (QoS) delay constraints, captured through each user's effective capacity (EC). We propose novel closed-form expressions for the EC of the NOMA users and show that in the high signal to noise ratio (SNR) region, the “strong” NOMA user has a limited EC, assuming the same delay constraint as the “weak” user. We demonstrate that for the weak user, OMA achieves higher EC than NOMA at small values of the transmit SNR, while NOMA outperforms OMA in terms of EC at high SNRs. On the other hand, for the strong user the opposite is true, i.e., NOMA achieves higher EC than OMA at small SNRs, while OMA becomes more beneficial at high SNRs. This result raises the question of introducing “adaptive” OMA/NOMA policies, based jointly on the users' delay constraints as well as on the available transmit power.

Finite blocklength (short packet) communications with non-orthogonal multiple access (NOMA) is regarded as an enabler for ultra-reliable and low-latency communications (URLLC). In this paper, we investigate the link-layer rate, i.e., the effective capacity, of a two-user NOMA in finite blocklength regime. The delay performance of the NOMA users is analyzed by taking into consideration the queueing delay violation probability and the transmission error probability. We further provide closed-form expressions for the individual effective capacity of the NOMA users in Rayleigh fading environment. Through simulations, we investigate the impact of the transmit signal-to-noise ratio and the delay exponent on the achievable effective capacity and the queueing delay violation probability of the NOMA weak and strong users. In particular, results show that when using short-packet communications, the queueing delay violation probability cannot be improved below a threshold.

This paper studies the problem of secure communication from a transmitter to a receiver with the use of short packets under the existence of multiple eavesdroppers, who are overhearing the transmission. We assume that the eavesdroppers are mutually independent. Further, we consider that the main channel and eavesdropper channels are Rayleigh fading, then use the performance metric of average secrecy throughput to measure how secure the communication is. We derive a closed form approximation of the average secrecy throughput in the presence of multiple eavesdroppers. Finally, the approximation is validated through simulations and we have seen that the approximation is very close to the corresponding simulation results.

This paper investigates the performance of an uplink Non-orthogonal Multiple Access (NOMA) with discrete M-QAM modulation and fixed power coefficients. Specifically, an uplink NOMA with a base station and two users are considered and two different performance metrics, namely bit error rate and spectral efficiency, are investigated. We provide closed-form expressions for the average spectral efficiency of NOMA with M-QAM which shows that the performance of the weak user is limited to a certain value which depends on the power coefficients solely. Moreover, results of closed-form expressions and simulation are compared to verify the expressions and to analyze the performance of the proposed NOMA system. The simulation results show that increasing the power coefficient of weak user can improve the weak user's performance in high SNRs, but it does not work well in low SNRs.

In this paper, we analyze the performance of vehicular optical camera communication (OCC) towards ultra-reliable and low latency communications (uRLLC). The employed vehicular OCC model uses light-emitting diodes (LED) as transmitter and camera as receiver. In particular, we investigate the performance of the proposed system in terms of bit error rate (BER), spectral efficiency, and transmission latency at different inter-vehicular distances and angle of incidences (AoI). Further, we investigate the use of adaptive modulation to improve the spectral efficiency. From our analysis, we note that by satisfying a given target BER, higher spectral efficiency and lower latency can be achieved through adjusting the AoI towards the smaller degrees and switching into the suitable modulation order. Finally, we verify the results through simulations, which show that OCC can ensure ultra-low latency as well as satisfy the reliability requirements in automotive vehicles.

This paper proposes a new power allocation scheme to jointly optimize energy efficiency (EE) and spectral efficiency (SE) of a point-to-point communication system in which the transmitter is equipped with fixed as well as energy harvesting batteries. Time switching protocol is used such that in each time frame the node either harvests energy or transmits information. Firstly, a multi-objective optimization problem which jointly optimizes EE and SE is formulated. An importance weight parameter is introduced to control the priority level between EE and SE. Secondly, the multi-objective problem is transformed into a single-objective optimization problem by using importance weight, and then solved through fractional programming. Using the Karush-Kuhn-Tucker conditions, the optimum power allocation scheme without input power constraint is developed. The ensuing solution is then generalized for system operation with average input power constraint. Closed-form expressions are derived and tested through simulations. Numerical results results are provided, and show the impact of the harvested power in improving the overall rate of the system. Also investigation is done to analyze the effect of system parameters on the achievable trade-off performance of the energy-harvesting based system.

This paper studies the performance of wireless power transfer in distributed antenna systems (DAS). In particular, the distributed remote radio heads (RRHs), which are conventionally distributed in the network to enhance the performance, are also used to increase the energy harvesting (EH) at the energy-constrained users. Based on this idea, the network area is divided into two zones, namely: 1) EH zone and 2) interference zone. The users in the EH zones are guaranteed to harvest sufficient energy from the closed RRH, while the users in the interference zones harvest energy from the surrounding RRHs. A harvest-then-transmit protocol is adopted, where in the power transfer phase the multiple antennas RRHs broadcast energy signals to the users. In the information transmission phase, the users utilize the harvested energy to transmit their signals to the RRHs. In addition, zero-forcing is applied at the RRHs receivers, to mitigate the interference. The system spectral efficiency is evaluated in two different scenarios based on the channel state information (CSI) namely: 1) CSI is unknown at the RRHs 2) CSI is perfectly known at the RRHs. In contrast to conventional EH-muliple-input multiple-output (MIMO) systems, performance analysis of EH DAS-MIMO is a challenging problem, because the channels are characterized by non-identical path-loss and EH effects which make the classical analytical methods non-tractable. In light of this, new analytical expressions of the ergodic spectral efficiency are derived and then Monte Carlo simulations are provided to verify the accuracy of our analysis. The effects of main system parameters on the EH-DAS performance are investigated. The results show that there is an optimal value of the EH time for each users locations that maximizes the system performance. In addition, size of the EH-zone area depends on the required harvested power at the users which is dependent essentially on the target spectral efficiency.

In this paper, a novel approach is introduced to study the achievable delay-guaranteed secrecy rate, by introducing the concept of the effective secrecy rate (ESR). This study focuses on the downlink of a non-orthogonal multiple access (NOMA) network with one base station, multiple single-antenna NOMA users and an eavesdropper. Two possible eavesdropping scenarios are considered: 1) an internal, unknown, eavesdropper in a purely antagonistic network; and 2) an external eavesdropper in a network with trustworthy peers. For a purely antagonistic network with an internal eavesdropper, the only receiver with a guaranteed positive ESR is the one with the highest channel gain. A closed-form expression is obtained for the ESR at high signal-to-noise ratio (SNR) values, showing that the strongest user’s ESR in the high SNR regime approaches a constant value irrespective of the power coefficients. Furthermore, it is shown the strongest user can achieve higher ESR if it has a distinctive advantage in terms of channel gain with respect to the second strongest user. For a trustworthy NOMA network with an external eavesdropper, a lower bound and an upper bound on the ESR are proposed and investigated for an arbitrary legitimate user. For the lower bound, a closed-form expression is derived in the high SNR regime. For the upper bound, the analysis shows that if the external eavesdropper cannot attain any channel state information (CSI), the legitimate NOMA user at high SNRs can always achieve positive ESR, and the value of it depends on the power coefficients. Simulation results numerically validate the accuracy of the derived closed-form expressions and verify the analytical results given in the theorems and lemmas.

This paper analyzes the ergodic secrecy capacity of an energy-constrained multiple-antennas amplify-and-forward (AF) relaying system in the presence of a passive eavesdropper. In the first phase, the source broadcasts information signal, while the destination sends an artificial jamming signal. The jamming signal has two main purposes: 1) enhancing the system security; 2) increasing the energy harvesting (EH) at the relay node. In the second phase, the relay uses the harvested energy to amplify and forward the received signal to the destination. For this system model, explicit mathematical expressions for the ergodic secrecy capacity are derived for three different common EH-relaying protocols, namely, power splitting relaying (PSR), antenna selection and power splitting (ASPS) receiver, and ideal relaying receiver (IRR). Monte-Carlo simulations are included to validate the analysis and the effect of different parameters on the system security are investigated. The results show that, the ASPS receiver outperforms PSR in terms of secrecy capacity.

In this paper, we consider an energy harvesting (EH)-based relaying system where an EH-source node equipped with a rechargeable battery to store the energy harvested from the environment, communicates with a destination with the help of a relay node. The relay and destination both have an unlimited power supply, while the source relies solely on the harvested energy. A delay-limited transmission mode is assumed in this paper, in which if the source data cannot be transmitted within a delay deadline, it will be lost. Based on this model, an efficient adaptive source transmission policy is proposed. Markov chain analysis is considered to model the levels of the stored energy at the source node and the system performance is evaluated in terms of the transmission and success probabilities. The results reveal that the benefit of the proposed transmission strategy in delay-limited applications is highly dependent on the proper choice of the system design parameters and the harvested energy per packet.

The increasing adoption of the Internet of Things has led to the need for systems with higher spectral and energy efficiency (EE) in order to enable communication. Larger data rate demands had led researchers to look at millimeter wave (mmWave) bands to boost network rates. This paper investigates the downlink performance of a three-tier heterogeneous network that consists of sub-6 GHz macrocells overlaid with small cells operating on both the mmWave and sub-6 GHz bands. A model is developed using tools from stochastic geometry to analyze the coverage, rate, area spectral efficiency, and EE of such a network. Various deployment strategies and their impacts on the considered metrics are studied. Simulation results are used to verify the validity of the proposed model.

This paper focuses on the performance evaluation of an energy harvesting (EH) equipped dual-hop relaying system for which the end-to-end signal-to-noise ratio (SNR) and the overall system throughput are analyzed. The transmitter and relay nodes are equipped with both fixed and EH batteries. The source for harvesting at the transmitter is the solar energy, and at the relay node, the interference energy in the radio frequency is the harvesting source. Time switching scheme is used at the relay to switch between EH and decoding information. Harvest-use approach is implemented, and we investigate the effects of the harvesting energy in enhancing the performance of the relaying system by deriving estimated closed-form expressions for the cumulative distribution function of each link's individual SNR and of the end-to-end SNR. The analytical expression for the ergodic capacity is also derived. These expressions are validated through Monte-Carlo simulations. It is also shown that with the additional EH at the transmitter (source and relay), a significant improvement in the system throughput can be achieved when fixed batteries are running on low powers.

In this paper, we study the achievable link-layer rate, namely, effective capacity (EC), under the per-user statistical delay quality-of-service (QoS) requirements, for a downlink non-orthogonal multiple access (NOMA) network with M users. Specifically, the M users are assumed to be divided into multiple NOMA pairs. Conventional orthogonal multiple access (OMA) then is applied for inter-NOMA-pairs multiple access. Focusing on the total link-layer rate for a downlink M-user network, we prove that OMA outperforms NOMA when the transmit signal-to-noise ratio (SNR) is small. On the contrary, simulation results show that NOMA prevails over OMA at high values of SNR. Aware of the importance of a two-user NOMA network, we also theoretically investigate the impact of the transmit SNR and the delay QoS requirement on the individual EC performance and the total link-layer rate for a two-user network. Specifically, for delay-constrained and delay-unconstrained users, we prove that for the user with the stronger channel condition in a two-user network, NOMA prevails over OMA when the transmit SNR is large. On the other hand, for the user with the weaker channel condition in a two-user network, it is proved that NOMA outperforms OMA when the transmit SNR is small. Furthermore, for the user with the weaker channel condition, the individual EC in NOMA is limited to a maximum value, even if the transmit SNR goes to infinity. To confirm these insightful conclusions, the closed-form expressions for the individual EC in a two-user network, by applying NOMA or OMA, are derived for both users and then confirmed using Monte Carlo simulations.

Millimeter wave (mmWave) links have the potential to offer high data rates and capacity needed in fifth generation (5G) networks, however they have very high penetration and path loss. A solution to this problem is to bring the base station closer to the end-user through heterogeneous networks (HetNets). HetNets could be designed to allow users to connect to different base stations (BSs) in the uplink and downlink. This phenomenon is known as downlink-uplink decoupling (DUDe). This paper explores the effect of DUDe in a three tier HetNet deployed in two different real-world environments. Our simulation results show that DUDe can provide improvements with regard to increasing the system coverage and data rates while the extent of improvement depends on the different environments that the system is deployed in.

The existing cellular networks are being modified under the umbrella of fifth generation (5G) networks to provide high data rates with optimum coverage. Current cellular systems operating in ultra high frequency (UHF) bands suffer from severe bandwidth congestion hence 5G enabling technologies such as millimeter wave (mmWave) networks focus on significantly higher data rates. In this paper, we explore the impact of co-existance of massive Multiple-Input Multiple-Output (MIMO) that provides large array gains and mmWave small cells on coverage. We investigate the downlink performance in terms of coverage and rate of a three tier network where a massive MIMO macro base stations (MBSs) are overlaid with small cells operating at sub-6GHz and mmWave frequency bands. Based on the existing stochastic models, we investigate user association, coverage probability and data rate of the network. Numerical results clearly show that massive MIMO enabled MBSs alongside mmWave small cells enhance the performance of heterogeneous networks (HetNets) significantly.

In this paper, the total system effective capacity (EC) maximization problem for the uplink transmission, in a multi-user multi-carrier orthogonal frequency division multiple access system, is formulated as a combinatorial integer programming problem, subject to each user's link-layer energy efficiency (EE) requirement as well as the individual's average transmission power limit. To solve this challenging problem, we first decouple it into a frequency provisioning problem and an independent multi-carrier link-layer EE-EC tradeoff problem for each user. In order to obtain the subcarrier assignment solution, a low-complexity heuristic algorithm is proposed, which not only offers close-to-optimal solutions, while serving as many users as possible, but also has a complexity linearly relating to the size of the problem. After obtaining the subcarrier assignment matrix, the multi-carrier link-layer EE-EC tradeoff problem for each user is formulated and solved by using Karush-Kuhn-Tucker conditions. The per-user optimal power allocation strategy, which is across both frequency and time domains, is then derived. Further, we theoretically investigate the impact of the circuit power and the EE requirement factor on each user's EE level and optimal average power value. The low-complexity heuristic algorithm is then simulated to compare with the traditional exhaustive algorithm and a fair-exhaustive algorithm. Simulation results confirm our proofs and design intentions, and further show the effects of delay quality-of-service exponent, the total number of users, and the number of subcarriers on the system tradeoff performance.

In this paper, we develop and analyze a novel performance metric, called interference efficiency, which shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the interference efficiency of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power, total transmit power, and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP) that aims to maximize ergodic sum rate of SUs and to minimize average interference power on the primary receiver. We solve the MOP by first transferring it into a single objective problem (SOP) using a weighted sum method. Considering different scenarios in terms of channel state information (CSI) availability to the SU transmitter, we investigate the effect of CSI on the performance and power allocation of the SUs. When full CSI is available, the formulated SOP is nonconvex and is solved using augmented penalty method (also known as the method of multiplier). When only statistical information of the channel gains between the SU transmitters and the PU receiver is available, the SOP is solved using Lagrangian optimization. Numerical results are conducted to corroborate our theoretical analysis.

Millimeter wave (mmWave) technology integrated with heterogeneous networks (HetNets) has emerged as a new wave to overcome the thirst for higher data rates and severe shortage of spectrum. In this paper, we consider the uplink of a hybrid HetNet with femtocells overlaid on a macrocell, and formulate a two layer game theoretic framework to maximise the energy efficiency (EE) while optimising the network resources. The outer layer allows each femtocell access point (FAP) to maximise the data rate of its users by selecting the frequency band either from the sub-6 GHz and the mmWave. The solution to this non-cooperative game can be obtained by using pure strategy Nash equilibrium. The inner layer ensures the energy efficient user association method subject to the minimum rate and maximum transmission power constraints by using dual de-composition approach. Simulation results show that the proposed hybrid HetNet scheme exploiting the mmWave frequency band improves the sum-rate and EE in comparison to the scenario where all the networks operate at sub-6 GHz frequency band. The performance can further be enhanced by incorporating the power control mechanism.

In this paper, we investigate the achievable energy efficiency of cognitive radio networks where two main modes are of interest, namely, spectrum sharing (known as underlay paradigm) and spectrum sensing (or interweave paradigm). In order to improve the energy efficiency, we formulate a new multiobjective optimization problem that jointly maximizes the ergodic capacity and minimizes the average transmission power of the secondary user network while limiting the average interference power imposed on the primary user receiver. The multiobjective optimization will be solved by first transferring it into a single objective problem (SOP), namely, a power minimization problem, by using the ε-constraint method. The formulated SOP will be solved using two different methods. Specifically, the minimum power allocation at the secondary transmitter in a spectrum sharing fading environment are obtained using the iterative search-based solution and augmented Lagrangian approach for single and multiple secondary links, respectively. The significance of having extra side information and also imperfect side information of cross channels at the secondary transmitter are investigated. The minimum power allocations under perfect and imperfect sensing schemes in interweave cognitive radio networks are also found. Our numerical results provide guidelines for the design of future cognitive radio networks.

A joint optimization problem of link-layer energy efficiency (EE) and effective capacity (EC) in a Nakagami-m fading channel under a delay-outage probability constraint and an average transmit power constraint is considered and investigated in this paper. First, a normalized multi-objective optimization problem (MOP) is formulated and transformed into a single-objective optimization problem (SOP), by applying the weighted sum method. The formulated SOP is then proved to be continuously differentiable and strictly quasiconvex in the optimum average input power, which turns out to be a cup shape curve. Furthermore, the weighted quasiconvex tradeoff problem is solved by first using Charnes-Cooper transformation and then applying Karush-Kuhn-Tucker (KKT) conditions. The proposed optimal power allocation, which includes the optimal strategy for the link-layer EE-maximization problem and the EC-maximization problem as extreme cases, is proved to be sufficient for the Pareto optimal set of the original EE-EC MOP. Moreover, we prove that the optimum average power level monotonically decreases with the importance weight, but strictly increases with the normalization factor, the circuit power and the power amplifier efficiency. Simulation results confirm the analytical derivations and further show the effects of fading severeness and transmission power limit on the tradeoff performance.

Green Small Cell Networks aim at achieving high rates and low powers by offloading users with low signal-to-noise-ratios from macrocell to the pico base station. In this work, we propose to jointly optimise energy efficiency (EE) and spectrum efficiency (SE) such that the network providers can dynamically tune the trade-off parameter for different design requirements. This paper formulates the EE-SE trade-off as a multi-objective optimisation problem (MOP) in the uplink of multi-user two-tier Orthogonal Frequency Division Multiplexing Heterogeneous Networks. Using the weighted sum method, the MOP can be transformed into a single-objective optimisation problem (SOP). The proposed EE and SE trade-off optimisation problem is strictly quasi-concave. Hence, using Dual Decomposition approach, we derive the unique optimal solution. Numerical results demonstrate the effectiveness of the proposed approach and illustrate the fundamental tradeoff between EE and SE for different tradeoff parameters such as maximum transmission power and circuit power.

This paper proposes a new power allocation technique to jointly optimize link-layer energy efficiency (EE) and effective capacity (EC) of a Rayleigh flat-fading channel with delay-outage probability constraints. Specifically, EE is formulated as the ratio of EC to the sum of transmission power and rate-independent circuit power consumption. A multi-objective optimization problem (MOP) to jointly maximize EE and EC is then formulated. By introducing importance weight into the MOP, we can flexibly change the priority level of EE and EC, and convert the MOP into a single-objective optimization problem (SOP) which can be solved using fractional programming. At first, for a given importance weight and a target delay-outage probability, the optimum average transmission power level to maximize the SOP is found. Then, the optimal power allocation strategy is derived based on the obtained average input power level. Simulation results confirm the analytical derivations and further show the effects of circuit power, importance weight, and transmission power constraint limit on the achievable tradeoff performance.

This paper presents the three-fold energy, rate and delay tradeoff in mobile multimedia fading channels. In particular, we propose a rate-efficient power allocation strategy for delay-outage limited applications with constraints on energy-per-bit consumption of the system. For this purpose, at a target delay-outage probability, the link-layer energy efficiency, referred to as effective-EE, is measured by the ratio of effective capacity (EC) and the total expenditure power, including the transmission power and the circuit power. At first, the maximum effective-EE of the channel at a target delay-outage probability is found. Then, the optimal power allocation strategy is obtained to maximize EC subject to an effective-EE constraint with the limit set at a certain ratio of the maximum achievable effective-EE of the channel. We then investigate the effect of the circuit power level on the maximum EC. Further, to set a guideline on how to choose the effective-EE limit, we obtain the transmit power level at which the rate of increasing EC (as a function of transmit power) matches a scaled rate of losing effective-EE. Analytical results show that a considerable EC-gain can be achieved with a small sacrifice in effective-EE from its maximum value. This gain increases considerably as the delay constraint becomes tight.

This paper presents a delay-QoS-driven spectrum and energy efficiency optimization transmission technique. In particular, considering the cross-layer effective capacity (EC) model in Rayleigh fading channels, a spectrum- and energy-efficient power allocation strategy is proposed when maximum spectrum efficiency is achieved under minimum energy efficiency (EE) requirement. For this purpose, at a target delay-outage probability, the spectrum efficiency is measured by the EC. Further, the EE is formulated as the ratio of the EC to the total expenditure power. At first, the maximum achievable EE of the link at the target delay-outage probability is found. Then, the optimal power allocation strategy is obtained to maximize the EC subject to a minimum EE constraint set at a certain ratio of the maximum achievable EE. We prove that the optimization problem is a concave maximization problem and develop the global optimal solution. The analytical results show that a considerable EC-gain can be achieved with a small sacrifice in EE. This gain increases considerably as the delay constraint becomes tight.

This paper presents an energy-efficient power allocation strategy for Nakagami-m flat-fading channels with a delay-outage probability constraint. The operating input transmit power value is limited to Pmax. The energy efficiency (EE), expressed in units of b/J/Hz, is represented as the ratio of the effective capacity to the sum of transmission power (Pt) and circuit power (Pc). Since the EE-maximization objective function is quasi-concave, a unique global maximum exists. By using fractional programming, we develop an EE-optimal power allocation strategy that consists of two steps: 1) obtaining the power level P̅un, at which the maximum EE can be achieved, and 2) distributing the power optimally based on the minimum of Pmaxand P̅un. We prove that while P̅unmonotonically increases with Pc, the maximum achievable EE is a monotonically decreasing function of Pc. The analysis further allows us to derive the EE of three important cases: non-fading channels, extremely stringent delay-limited systems, and systems with no delay constraints. Simulation results confirm analytical derivations and further show the effects of the circuit power, fading duration, and fading severeness on the achievable EE and effective capacity of a delay-limited fading channel.

In this paper, we maximize the parameterized energy efficiency (EEP) of a multi-channel fading communication link that simultaneously transmits data corresponding to delay-sensitive and delay-insensitive applications subject to a constraint on the minimum effective capacity (EC) of delay-sensitive traffic. EEP, in b/s/Hz, is defined as the difference between the spectral efficiency (SE) and the transmit power scaled by a parameter which represents the penalty on the transmit power. We provide an optimal power adaptation policy to this problem which is either given by the global optimum, if feasible, or given by the boundary point where the objective function intersects the constraint. Further, we apportion the total transmit power into delay-sensitive power, which is the minimum power required to meet the EC constraint and delay-insensitive power, which is the residual power used to maximize the EEP of the link. Simulation results show that delay-sensitive power is an exponentially increasing function of minimum EC while delay-insensitive power decays to zero for higher values of minimum EC. Further, delay-insensitive power increases while delay-sensitive power exponentially decreases with number of subchannels in the system.

This paper presents an optimal energy-efficient power allocation scheme for a point-to-point multicarrier link over frequency-selective fading channel subject to a delay-outage probability constraint. For a target delay-outage limit, the energy efficiency (EE) objective function is formulated as the ratio of the achieved link effective capacity to the total expenditure power, expressed in units of b/J/Hz. We first prove that this objective function is quasi-concave in the transmission power, and, hence, the global maximum solution of the underlying optimization problem can be obtained using fractional programming. Subsequently, we develop a two-step optimal power allocation algorithm by first obtaining the average sum power level corresponding to the maximum achievable EE, followed by jointly distributing this obtained average power over time and frequency. Analytical results show that the EE-based power allocation has a structure similar to that of the QoS-driven spectral-efficient scheme, but with a different cut-off threshold below which no transmission power is allocated. Simulation results show that the proposed joint optimal power allocation scheme provides significant EE gains over the simple independent subcarrier optimization scheme, where these performance advantages become more pronounced with tighter delay constraints and in fading channels with more severe frequency selectivity.

This paper proposes joint user association and energy-efficient resource allocation in the uplink of multi-user two-tier Orthogonal Frequency Division Multiplexing (OFDM) Heterogeneous Networks (HetNets) subject to user's maximum transmission power and minimum-rate constraints. The proposed scheme aims at achieving high rates at low powers satisfying the user's quality-of-service (QoS) constraints (in terms of minimumrate requirements) by offloading the users with low signal to noise ratio (SNR) from macrocell to the pico base station (BS). A channel-to-noise-ratio (CNR)-based rate proportional resource allocation approach is proposed to transform the minimumrate constraint into a minimum required transmission power constraint on each subcarrier. The single-user single-carrier and multi-user multi-carrier energy efficiency (EE) maximization problems are then solved under maximum and minimum power constraints using Karush-Kuhn-Tucker (KKT) conditions. The impact of users' maximum transmission power and minimumrate requirements on EE and throughput are investigated through illustrative results. The rate-proportional approach is evaluated against the equal rate allocation approach for different user associations and various numbers of users, maximum transmission power, and circuit powers. Significant gains in EE can be achieved for the HetNets if the path loss based user association is combined with the proposed CNR rate proportional mechanism.

Spectral efficiency (SE) is one of the key performance indicators of wireless communications, and energy efficiency (EE) is an urgent need to tackle the challenges raised by the high demands of wireless traffics and energy consumption. However, these two important design criteria conflict with each other and a careful study of their trade-off is mandatory for designing future wireless communication systems. In this paper, we introduce an optimization problem to maximize the ergodic SE of a point-to-point communication link with a constraint on its minimum ergodic EE. We prove that, at optimality, the constraint on minimum EE is met with equality, and use it to provide a closed-form expression for finding the optimal water-filling level in a Nakagami-m fading channel with integer values of m. We exploit this formulation to investigate the relationship between SE and EE as a function of circuit power, power amplifier (PA) efficiency and channel power gain. We observe that the SE and EE always contradict with each other, however, the trade-off curve is non-linear. The curve is steeper at the extremities as compared to the middle region. Hence, a small sacrifice in EE from its maximum value may map into a significant gain in SE. Our simulations show that this gain in SE is a decreasing function of the circuit power and channel power gain while an increasing function of the PA efficiency.

This study investigates the capacity of multiple relay channels in different fading and shadowing environments under spectrum‐sharing constraints. The authors consider that a secondary user (SU) is allowed to share the spectrum band with a primary user (PU) provided that the SU's transmit power remains below an interference power threshold set by the PU. Considering a scenario where the SU's transmitter and receiver cannot communicate directly, a relay node, chosen among a set of K terminals, helps transmitting data from the SU's transmitter to the destination. The SU's transmitter and chosen relay node adapt their corresponding transmission parameters so as to satisfy the interference‐power constraint at the PU's receiver. The authors derive closed‐form expressions for the ergodic capacity of the SU's channel in Rayleigh fading, Nakagami‐ m fading and lognormal shadowing environments. They further obtain the outage capacity assuming the aforementioned environments and the above‐mentioned spectrum‐sharing limitations. Numerical results are provided to reinforce our theoretical derivations.

This paper presents an energy-efficient power allocation for a multicarrier link over a frequency-selective fading channel with a delay-outage probability constraint. The power adaptation maximizes the system energy efficiency (EE), formulated as the ratio of the achieved effective capacity (EC) to the total expenditure power, including both transmission power and rate-independent circuit power. We prove that this objective function is quasi-concave in the transmission power, and derive the global optimum solution using fractional programming. Based on the obtained solution, we develop a power adaptation algorithm consisting of two steps: (i) establishing the optimum average power level corresponding to the maximum achievable EE with no transmit power constraint, and then (ii) for a given power constraint, jointly distributing the power over time and frequency based on the constraint and the optimum power level found in the first step. Analytical results show that the proposed EE-based power allocation has a structure similar to the allocation that maximizes the EC, but with a different cut-off threshold. Our proposed joint EE-optimal power allocation provides significant EE gains over both the joint spectral-efficient and independent-subcarrier EE-based power allocation schemes, where the rate-energy tradeoff becomes more pronounced with higher frequency selectivity.

In this paper, we obtain an energy-efficient power allocation technique for a Rayleigh block-fading channel with delay-limited applications. In particular, we consider a probabilistic delay constraint as the user quality-of-service (QoS) requirement, and incorporate the concept of effective capacity to obtain the maximum arrival rate, at which, the delay constraint is satisfied. We obtain the energy efficiency (EE), which is formulated as the ratio between the effective capacity and the total expenditure power, of this system and derive the power allocation strategy that maximizes the EE. Numerical results are conducted to corroborate our theoretical results. In addition, for comparison reasons, we plot the maximum achievable EE under two well-known power allocations schemes, namely, water-filling (wf) and constant power allocation (cons) when considering delay constraints. The results show that in stringent delay limited systems, adaptive power allocation improves the maximum achievable EE significantly.

In order to guarantee dual quality-of-service (QoS) measures, namely, packet error rate (PER) and delay constraint, in a spectrum-sharing channel, we propose a cross-layer resource allocation approach in this paper. In particular, we assume an underlay cognitive radio scenario, in which, a secondary user (SU) is granted access to the spectrum as long as its average interference power, imposed on the primary-user (PU) receiver is below a predefined threshold. The SU employs adaptive modulation and coding (AMC) at the physical layer and automatic repeat request (ARQ) at the link-layer. An adaptive power and rate allocation scheme is proposed for the SU transmitter to meet both the PER requirement and the statistical delay constraints. To this end, we use the effective capacity concept and obtain closed-form expressions for the power allocation and capacity of the SU's link in Nakagami-m fading channels.

In this paper, we consider the problem of energy-efficient resource and power allocation in the uplink of multiuser multi-channel Orthogonal Frequency Division Multiplexing (OFDM) based systems subject to constraints on user equipment (UE) transmit power. This problem is non-deterministic polynomial-time hard and an optimum solution for a system with U users and N resource units requires a complexity of at least O(NUN). Using an iterative solution approach, we propose two sub-optimal, yet efficient, scheduling algorithms that maximize the energy efficiency (EE) considering both UE circuit power (Pc) and rate-dependent transmit power with an upper limit of Pmax. Simulation results show that the proposed algorithms provide near-optimal solutions with much lower computational burden of O(UN) and O(UN2/2). Further performance studies indicate that the proposed algorithms can offer an EE of more than 2 times with a throughput reduction of less than 13% as compared to the spectral-efficient greedy algorithm. Our studies also reveal that the EE is quickly increased with Pmaxwhen ≪ Pcand then reach saturation as Pmax approaches Pc.

We propose a novel signal to interference and noise (SINR) balancing technique for a downlink cognitive radio network (CRN) wherein multiple cognitive users (also referred to as secondary users (SUs)) coexist and share the licensed spectrum with the primary users (PUs) using the underlay approach. The proposed beamforming technique maximizes the worst SU SINR while ensuring that the interference leakage to PUs is below specific thresholds. Due to the additional interference constraints imposed by PUs, the principle of uplink-downlink duality used in the conventional downlink beamformer design cannot be directly applied anymore. To circumvent this problem, using an algebraic manipulation on the interference constraints, we propose a novel SINR balancing technique for CRNs based on uplink-downlink iterative design techniques. Simulation results illustrate the convergence and the optimality of the proposed beamformer design.

We consider a network of cognitive users (also referred to as secondary users (SUs)) coexisting and sharing the spectrum with primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we consider a CRN wherein the number of SUs requesting channel access exceeds the number of available frequency bands and spatial modes. In such a setting, we propose a joint fast optimal resource allocation and beamforming algorithm to accommodate maximum possible number of SUs while satisfying quality of service (QoS) requirement for each admitted SU, transmit power limitation at the secondary network basestation (SNBS) and interference constraints imposed by the PUs. Recognizing that the original user maximization problem is a nondeterministic polynomial-time hard (NP), we use a mixed-integer programming framework to formulate the joint user maximization and beamforming problem. Subsequently, an optimal algorithm based on branch and bound (BnB) method has been proposed. In addition, we propose a suboptimal algorithm based on BnB method to reduce the complexity of the proposed algorithm. Specifically, the suboptimal algorithm has been developed based on the first feasible solution it achieves in the fast optimal BnB method. Simulation results have been provided to compare the performance of the optimal and suboptimal algorithms.

In this paper, we consider coexistence of secondary and primary users who share particular portions of the spectrum and propose a delay-constrained power and rate allocation scheme for the secondary user link. Secondary users are allowed to access the spectrum occupied by a primary user subject to satisfying interference-power limitations imposed by the primary user. Applying this limitation, we obtain the maximum arrival-rate supported by the secondary channel in Nakagami-m block-fading environment subject to satisfying a given statistical delay quality-of-service (QoS) constraint. In this respect, we derive the optimal rate and power adaptation policy that maximizes the effective capacity of the channel, and provide closed-form expressions for the power allocation and the effective capacity. In addition, we obtain closed-form expressions for the expenditure-power that is required at the secondary transmitter to achieve the above-mentioned capacity metric. Moreover, for comparison purposes, we consider two widely deployed power allocation strategies, namely, optimal power and rate allocation (opra) and channel inversion with fixed rate (cifr), and investigate the effective capacity of the channel under these power transmission techniques. Numerical simulations are conducted to corroborate our theoretical results.

This paper investigates delay constrained performance of a cognitive radio relay network when the cognitive (secondary) user transmission is subject to satisfying spectrum-sharing restrictions imposed by a primary user. The primary user allows a secondary user to gain access to its allocated spectrum band as long as certain thresholds on the interference power, on the peak or average values, inflicted on the primary receiver are not exceeded by the transmission of the secondary users. In addition, we assume that the secondary transmitter benefits from an intermediate node, chosen from K terminals, to relay its signal to the destination. Considering that the transmission of the secondary user is subject to satisfying a statistical delay quality-of-service (QoS) constraint, we study the maximum arrival rate of the secondary user's relay link while the interference limitations required by the primary user are satisfied. Particularly, we obtain the effective capacity of the secondary network and determine the power allocation policies that maximize the effective capacity of the secondary user's relaying channel. In addition, we derive closed-form expressions for the effective capacity of the channel in Rayleigh block-fading environment under peak or average interference-power constraints. Numerical simulations are provided to endorse our theoretical results.

In this paper, we consider variable-rate variable-power MQAM modulation employed under delay quality-of-service (QoS) constraints over spectrum-sharing channels. In particular, we assume two users sharing the spectrum with one of them having a primary access to the band, and the other, known as secondary user, constrained by interference limitations imposed by the former. We study the performance of the secondary user's link employing adaptive MQAM modulation scheme when, on top of the above-mentioned interference constraint, the secondary user is also required to satisfy a statistical delay QoS constraint. Considering two modulation schemes, namely, continuous MQAM and discrete MQAM with restricted constellations, we obtain the effective capacity of the secondary user's link, and derive the optimum power allocation scheme that maximizes the effective capacity in each case. Numerical simulations are conducted to corroborate our theoretical results.

In this paper, we investigate the performance gains of cognitive radio relay networks under delay quality of service (QoS) limitations at the secondary users, and spectrum-sharing restrictions imposed by the primary users of the channel. In particular, we assume that the primary user allows secondary users to gain access to its allocated spectrum band as long as a certain threshold on its corresponding outage probability is satisfied. Using this constraint, we find the maximum limit on the interference-power inflicted on the primary receiver that should not be exceeded by the transmission of the secondary users. In addition, we assume that the secondary transmitter benefits from an intermediate node, chosen from K terminals, to relay its signal to the destination. Considering that the transmission of the secondary user is subject to satisfying a statistical delay QoS constraint, we obtain the maximum arrival-rate supported by the secondary user's relaying link. In this respect, we derive closed-form expressions for the effective capacity of the channel in Rayleigh block-fading environment. Numerical simulations are provided to endorse our theoretical results.

In this paper, we analyze the capacity gains of opportunistic spectrum-sharing channels in fading environments with imperfect channel information. In particular, we consider that a secondary user may access the spectrum allocated to a primary user as long as the interference power, inflicted at the primar's receiver as an effect of the transmission of the secondary user, remains below predefined power limits, average or peak, and investigate the capacity gains offered by this spectrum-sharing approach when only partial channel information of the link between the secondaryiquests transmitter and primary's receiver is available to the secondary user. Considering average received-power constraint, we derive the ergodic and outage capacities along with their optimum power allocation policies for Rayleigh flat-fading channels, and provide closedform expressions for these capacity metrics. We further assume that the interference power inflicted on the primaryiquests receiver should remain below a peak threshold. Introducing the concept of interference-outage, we derive lower bounds on the ergodic and outage capacities of the channel. In addition, we obtain closedform expressions for the expenditure-power required at the secondary transmitter to achieve the above-mentioned capacity metrics. Numerical simulations are conducted to corroborate our theoretical results.

This paper investigates the fundamental capacity limits of opportunistic spectrum-sharing channels in fading environments. The concept of opportunistic spectrum access is motivated by the frontier technology of cognitive radio which offers a tremendous potential to improve the utilization of the radio spectrum by implementing efficient sharing of the licensed spectrum. In this spectrum-sharing technology, a secondary user may utilize the primary user's licensed band as long as its interference to the primary receiver remains below a tolerable level. Herein, we consider that the secondary user's transmission has to adhere to limitations on the ensuing received power at the primary's receiver, and investigate the capacity gains offered by this spectrum-sharing approach in a Rayleigh fading environment. Specifically, we derive the fading channel capacity of a secondary user subject to both average and peak received-power constraints at the primary's receiver. In particular, considering flat Rayleigh fading, we derive the capacity and optimum power allocation scheme for three different capacity notions, namely, ergodic, outage, and minimum-rate, and provide closed-form expressions for these capacity metrics. Numerical simulations are conducted to corroborate our theoretical results.

In this paper, we propose a quality-of-service (QoS) constrained power and rate allocation scheme for spectrum sharing systems. In particular, we assume existence of secondary users, who are allowed to access the spectrum occupied by a primary user subject to satisfying interference-power limitations. Specifically, we assume that the successful operation of the primary user requires a minimum-rate to be supported by its channel for a certain percentage of time, and obtain an average interference-power constraint that is required to be fulfilled by the secondary user. Applying this limitation, we obtain the maximum arrival-rate supported by a Rayleigh block- fading channel subject to satisfying a given statistical delay QoS constraint. In this respect, we derive an optimal adaptation policy that maximizes the effective capacity of the channel, and provide closed-form expressions for the power allocation and the effective capacity. In addition, we obtain closed-form expressions for the expenditure-power that is required at the secondary transmitter to achieve the above-mentioned capacity metric.

In cognitive radio technology, secondary users may be granted access to the spectrum bands occupied by a primary user as long as the interference-power, inflicted on the primary receiver as an effect of the transmission of the secondary user, is deemed unharmful. In this paper, we assume that the successful operation of the primary user requires a minimum-rate to be guaranteed by its channel for a certain percentage of time, and obtain the interference-power constraint that is required to he fulfilled by the secondary user. We investigate the capacity gains offered by this spectrum-sharing approach when the input transmit power of the secondary user is limited. In particular, we assume that only partial channel information of the link between the secondary's transmitter and primary's receiver is available to the former, and derive lower bounds on the capacity of a Rayleigh flat-fading channel with different transmission techniques, namely, channel inversion and constant-power transmission. Closed-form expressions for these capacity metrics are provided, and numerical simulations are conducted to corroborate our theoretical results.

Cognitive radio technology has been recently proposed for sharing and utilising the spectrum in order to satisfy the increasing demands for spectrum access. In this radio technology, secondary users may be granted access to the spectrum bands occupied by a primary user as long as the interference power, inflicted on the primary receiver as an effect of the transmission of the secondary user, is deemed unharmful. In this paper the authors assume that the successful operation of the primary user requires a minimum rate to be guaranteed by its channel for a certain percentage of time and obtain the interference-power constraint that is required to be fulfilled by the secondary user. Considering the input transmit-power constraint, on average or peak power, for the secondary user, the authors investigate the capacity gains offered by this spectrum-sharing approach when only partial channel information of the link between the secondary's transmitter and primary's receiver is available to the former. In particular, the lower bounds on the capacity of a Rayleigh flat-fading channel with two different transmission techniques, namely channel inversion and optimum rate allocation with constant power transmission, are derived. Closed-form expressions for these capacity metrics are provided, and numerical simulations are conducted to corroborate the theoretical results.

We study upper and lower bounds on the achievable sum-rate of a correlated MIMO MAC with channel estimation error at the receiver when the correlation information is available to the users' transmitters, and prove that, for Gaussian input signals with arbitrary input covariance matrices, the gap between these bounds does not exceed a limiting value at any input transmit power. We further prove that in systems with uniform input power utilization over the transmit antennas, the gap between the mutual information bounds increases monotonically as the input power of each user increases. Furthermore, we show that in the absence of correlation, the gap between the mutual information bounds is maximum for beamforming and minimum for uniform input power allocation over the transmit antennas. We further prove that utilizing the input power of each user towards the directions of the eigenvectors of its transmit correlation matrix maximizes the mutual information lower bound. Moreover, we derive the transmit directions that maximize the mutual information lower and upper bounds in an uncorrelated MIMO MAC with delayed feedback from the receiver to the transmitters, and characterize the power allocation of this system in terms of its beamforming range. Numerical simulations are conducted to corroborate our theoretical results.

In this paper, we focus on opportunistic spectrum- sharing channels, whereby a secondary user may access the spectrum owned by a primary user as long as the average interference power, inflicted at the primary's receiver as an effect of the transmission power of the secondary user, remains below a predefined threshold, and investigate the effect of imperfect feedback on the capacity gains offered by this spectrum-sharing approach in fading environments. In particular, we assume that the secondary user is only provided with partial channel information of the link between its transmitter and the primary's receiver and derive the ergodic and outage capacities achieved by the secondary user's channel, modeled as Rayleigh flat-fading, and provide closed-form expressions for these capacity metrics along with their optimum power allocation policies. We further obtain closed-form expressions for the outage probability and the expenditure-power required at the secondary transmitter to achieve the channel capacity. Numerical simulations are conducted to corroborate our theoretical results and quantify the effect of imperfect channel estimation.

In this paper, we study upper and lower bounds on the achievable sum-rate of an uncorrelated multiple-input multiple-output (MIMO) multiple access channel (MAC) for Gaussian input signals and with channel estimation error at the receiver. We prove that the gap between the mutual information bounds does not exceed a certain value for arbitrary input covariance matrices and at any input transmit power. We also prove that in a MIMO MAC with uniform input power utilization over the transmit antennas, the gap between the mutual information bounds increases monotonically as the input power of each user increases. Furthermore, we show that the gap between the bounds is maximum when beamforming is applied at the transmitters of all users. We also derive the transmit directions that maximize the mutual information lower and upper bounds when delayed feedback is available from the receiver to the transmitters, and characterize the power allocation of this system in terms of its beamforming range. Numerical simulations are conducted to corroborate our theoretical results and quantify the effect of imperfect channel estimation.

In this fast growing technology world, where communications play a major rule for connecting people and machines together, the growth in wireless applications have caused an increasing demand for gaining access to the radio spectrum. However, the outdated spectrum utilization policies, imposed by the regulatory bodies in the past century, have caused the spectrum to look over-saturated. Recently, the concept of opportunistic spectrum access has been introduced as a tool to overcome the scarcity of the spectrum. The latter technology offers a tremendous potential to improve the utilization of the radio spectrum by implementing an efficient sharing of the licensed spectrum, whereby a secondary user may utilize the primary user's licensed band as long as its interference to the primary receiver remains below a tolerable level. In this paper, we investigate the capacity gains offered by this spectrum-sharing approach in Rayleigh fading environments. In particular, we derive the fading channel capacity of a secondary user subject to both average and peak received-power constraints at the primary's receiver. Considering both constraints, we derive the ergodic and outage capacities along with their optimum power allocation policies for Rayleigh flat-fading channel, and provide closed-form expressions for these capacity metrics. Furthermore, numerical simulations are conducted to corroborate our theoretical results.

This paper investigates the effects of channel estimation error at the receiver on the achievable rate of distributed space-time block coded transmission. The authors assume that multiple transmitters cooperate to send the signal to the receiver and derive lower and upper bounds on the mutual information of STBCs when the sub-channel gains and error variances between different transmitter-receiver links are unequal. The authors prove that the gap between these two bounds can not exceed a certain value at high transmit powers. The authors further prove that the gap between the mutual information bounds increases monotonically as a function of the input transmit power, and show that the gap is minimum if the receiver can estimate the channels pertaining to different transmitters with the same accuracy. The authors further derive closed-form expressions for the outage probability lower bound of distributed-STBCs (D-STBCs) with arbitrary number of transmitters. Numerical simulations are conducted to corroborate the analysis and quantify the effect of imperfect channel estimation.

Orthogonal space-time block codes (STBCs) are known to orthogonalise the multiple-input multiple-output (MIMO) wireless channel, thus reducing the space-time vector detection to a simpler scalar detection problem. The capacity of STBCs over correlated Rayleigh and Ricean flat-fading MIMO channels under different adaptive transmitting techniques is studied. Three adaptive schemes known as optimal power and rate allocation, total channel inversion with fixed rate policy and its truncated variant are studied. Taking into account the effect of channel correlation, closed-form expressions are obtained for the capacity of orthogonalised Rayleigh and Ricean MIMO channels under these adaptive transmission techniques in order to avoid Monte-Carlo simulations.

In this paper, we study the capacity of space time block codes (STBCs) over correlated Rayleigh flat-fading MIMO channels combined with adaptive transmitting techniques. We study three adaptive schemes known as optimal power and rate allocation (opra), optimal rate allocation (ora), total channel inversion with fixed rate policy (cifr) and its truncated variant (tifr). We obtain closed form capacity expressions of STBCs combined with these adaptive schemes, taking into account the effect of channel correlation, hence avoiding numerical integrations or Monte-Carlo simulations

In this paper, we study the effect of channel estimation error at the receiver on the mutual information of a multi user multiple input multiple output (MIMO) channel obeying Rayleigh fading. We assume that imperfect knowledge of the channel is available at the receiver and find the upper bound and the lower bound on mutual information for Gaussian input signals for the uplink of this system. We prove that when the input power at each user is uniformly distributed over its transmit antennas, the bounds on the mutual information are asymptotically tight for Gaussian input signals and this tightness increases when the number of users increases. Numerical simulations are conducted to corroborate theoretical results.

In this paper, we study the effect of channel estimation error on transmitter design in a multiple input multiple output (MIMO) channel. We assume that only knowledge of either the channel correlation or mean is available at the transmitter and find the transmitting strategy. Under covariance feedback, at the transmitter the channel is modelled as a matrix of zero mean circularly symmetric complex Gaussian (ZMCSCG) random variables with known covariances. We assume that only rows of channel matrix are correlated. Under mean feedback the covariance of channel is modelled as white. We determine the necessary and sufficient conditions under which a unit rank input covariance matrix, i.e. eigen-beamforming, can achieve capacity lower bound. Numerical simulations are conducted to corroborate theoretical results.