Monostatic backscatter (MBS) networks provide connectivity for ultra-low power and low-cost tags for numerous applications. However, the reader operates in the full-duplex (FD) mode and experiences self-interference (SI) levels much higher (e.g., 160 dB) than the desired signal. However, hardware-based SI cancellation (SIC) techniques can remove SI partially only. Therefore, residual SI (RSI) dramatically degrades system performance. To remedy this problem, we develop a sum-rate maximization algorithm that suppresses the RSI and ensures that the tags harvest sufficient energy. It jointly optimizes the reader precoder and combiners and the tags reflection coefficients. Because of the non-convexity of this problem, we utilize alternating optimization (AO) to split it into three parts. They are then solved using successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques to yield the precoder, a generalized Rayleigh quotient-based closed-form solution for the combiners, and geometric programming (GP) to get the reflection coefficients. Simulation results validate the fast convergence of the algorithm and show significant sum rate improvements (more than 21%) over the baselines.

e investigate a wireless power transfer (WPT)-based backscatter-mobile edge computing (MEC) network with a reconfigurable intelligent surface (RIS).In this network, wireless devices (WDs) offload task bits and harvest energy, and they can switch between backscatter communication (BC) and active transmission (AT) modes. We exploit the RIS to maximize energy efficiency (EE). To this end, we optimize the time/power allocations, local computing frequencies, execution times, backscattering coefficients, and RIS phase shifts.e investigate a wireless power transfer (WPT)-based backscatter-mobile edge computing (MEC) network with a reconfigurable intelligent surface (RIS).In this network, wireless devices (WDs) offload task bits and harvest energy, and they can switch between backscatter communication (BC) and active transmission (AT) modes. We exploit the RIS to maximize energy efficiency (EE). To this end, we optimize the time/power allocations, local computing frequencies, execution times, backscattering coefficients, and RIS phase shifts.WThis goal results in a multi-objective optimization problem (MOOP) with conflicting objectives. Thus, we simultaneously maximize system throughput and minimize energy consumption via the Tchebycheff method, transforming into two single-objective optimization problems (SOOPs). For throughput maximization, we exploit alternating optimization (AO) to yield two sub-problems. For the first one, we derive closed-form resource allocations. For the second one, we design the RIS phase shifts via semi-definite relaxation, a difference of convex functions programming, majorization minimization techniques, and a penalty function for enforcing a rank-one solution. For energy minimization, we derive closed-form resource allocations. We demonstrate the gains over several benchmarks. For instance, with a 20-element RIS, EE can be as high as 3 (Mbits/Joule), a 150% improvement over the no-RIS case (achieving only 2 (Mbits/Joule)).

Non-orthogonal multiple access (NOMA) is an important part of the emerging fifth generation (5G) of mobile communications systems. NOMA schemes based on a long spreading mechanism, such as interleave division multiple access (IDMA), are among the main candidates for potential use in 5G. Interleave-based NOMA methods can provide a robust performance in highly interfered environments. In this paper, we present our performance evaluation results for IDMA and its simplified variants, namely, resource spreading multiple access (RSMA) and RSMA with interference cancellation (RSMA-SIC). In our evaluation, various interference scenarios, fading conditions and channel estimation errors are considered. Our results indicate that while IDMA offers the best performance, RSMA and RSMA-SIC may also maintain a respectable level of performance with a lower complexity.

A highly reliable transmission scheme based on a combined application of network coding and superposition modulation is introduced for a non- relay wireless communication system. It is shown that by employing superposition modulation, the side information needed for error recovery can be transmitted over the same set of resources as the original packets. A sub-constellation alignment mechanism for constructive combining of the least significant bits of the received symbols is proposed for efficient side information dissemination. The outage analysis and numerical results show that the proposed system can offer significant gains in link reliability.

This paper focuses on the design of vector perturbation (VP) precoding for multi-user multiple-input singleoutput downlink transmission under quantized channel state information. Each receiver decomposes its downlink channel vector in forms of channel direction information (CDI) and channel magnitude information (CMI) for feedback to the transmitter. Under quantized CDI and quantization error statistics, closed-form expressions to the mean-squared-error (MSE) between channel input and output when (i) perfect CMI available to the transmitter and (ii) only CMI statistics known at the transmitter, are derived. We then propose a unified approach to design the MSE minimization based VP precoders. Bit error rate simulation results indicate that the proposed VP precoder designs are less sensitive to quantization errors and CMI availability helps to improve the performance.

In this study, the authors propose simple methods to evaluate the achievable rates and outage probability of a cognitive radio (CR) link that takes into account the imperfectness of spectrum sensing. In the considered system, the CR transmitter and receiver correlatively sense and dynamically exploit the spectrum pool via dynamic frequency hopping. Under imperfect spectrum sensing, false‐alarm and miss‐detection occur which cause impulsive interference emerged from collisions due to the simultaneous spectrum access of primary and cognitive users. That makes it very challenging to evaluate the achievable rates. By first examining the static link where the channel is assumed to be constant over time, they show that the achievable rate using a Gaussian input can be calculated accurately through a simple series representation. In the second part of this study, they extend the calculation of the achievable rate to wireless fading environments. To take into account the effect of fading, they introduce a piece‐wise linear curve fitting‐based method to approximate the instantaneous achievable rate curve as a combination of linear segments. It is then demonstrated that the ergodic achievable rate in fast fading and the outage probability in slow fading can be calculated to achieve any given accuracy level.

We consider full-duplex (FD) bidirectional communication between a pair of nodes and investigate the impact of residual self-interference on sum-rate performance. We first analyze a situation where channel state information is available only at receiver (CSIR). For this case, we derive an exact expression and a lower bound to the sum-rate performance of FD and hence characterize the effect of residual self-interference. The study shows that, FD sum-rate performance is limited by the effective signal-to-residual self-interference power ratio (effective SIR). In particular, for a fixed effective SIR, FD achieves almost twice the sum-rate of half-duplex (HD) in low signal-to-noise ratio (SNR) regimes whilst FD performance is surpassed by HD in high SNR regions. A closed-form approximation to this crossover SNR is derived. We then investigate the sum-rate of FD assuming channel state information is available to both transmitter and receiver (CSIT). Comparison of FD sum-rates of CSIR and CSIT shows that, in low SNR regions, a significant benefit can be achieved with CSIT while the gain is small in high SNR levels.

In this paper, we rigorously analyze the optimal input distribution and capacity of an additive Bernoulli-Gaussian (BG) impulsive noise (IN) channel in high and low input power regimes. First, we obtain an input distribution for which the channel output is Gaussian distributed. This distribution, if valid, shall result in the capacity of the channel. At an asymptotically high input power level, we then show that the derived input is always valid and in fact, it resembles a Gaussian distribution. As such, the Gaussian channel input is considered approximately optimal. Using the monotonicity property of the characteristic function (CF), we then develop a necessary condition for the existence of the derived optimal input for a finite level of input power. The condition indicates that a sufficiently high input power is usually required. Then focusing on the low power region, we first derive an upper bound on the channel capacity assuming full knowledge of noise state. A closed-form expression of the mutual information (MI) achieved by Gaussian inputs, which is considered as a lower bound on the channel capacity, is then developed. By comparing these two bounds, it is shown that a Gaussian input asymptotically results in the capacity. Interestingly, it is also demonstrated that such a capacity is the same as the capacity of an erasure channel in low power regimes.

In this paper, we investigate the capacity limit of a single secondary user (SU) communication link in a cognitive radio system. An SU transmitter establishes the communication with its receiver by dynamically hopping in a frequency spectrum pool, and by sensing the spectrum to exploit the temporal communication opportunities. We characterize the performance of sensing by false-alarm and miss-detection probabilities. Firstly, focusing on a high channel input power region, we develop an upper bound on the SU capacity by assuming a Gaussian distributed output. A lower bound on the SU capacity is also derived using a Gaussian input. We then show that the lower bound closely approaches the upper bound at a high channel input power level. This means that the Gaussian input is nearly optimal in this case. Furthermore, we characterize the impact of primary user activities and sensing performance on the SU capacity by developing a closed-form tight approximation. Secondly, paying attention to a low channel input power region, we propose a genie-aided upper bound and a lower bound using the Gaussian input. By comparing these two bounds, a closed-form approximation to the capacity is developed and the near optimality of the Gaussian input is demonstrated. Finally, numerical results are provided to complement the theoretical discussion.

This paper studies the mutual information improvement attained by rotated multidimensional (multi-D) constellations via a unitary precoder G in Rayleigh fading. At first, based on the symmetric cut-off rate of the N-D signal space, we develop a design criterion with regard to the precoder G. It is then demonstrated that the use of rotated constellations in only a reasonably low dimensional signal space can significantly increase the mutual information in high-rate regimes. Based on parameterizations of unitary matrices, we then construct good unitary precoder G in 4-D signal space using a simple optimization problem, which involves only four real variables and it is applicable to any modulation scheme. To further illustrate the potential of multi-D constellation and to show the practical use of mutual information improvement, we propose a simple yet powerful bit-interleaved coded modulation (BICM) scheme in which a (multi-D) mapping technique employed in a multi-D rotated constellation is concatenated with a short-memory high-rate convolutional code. By using extrinsic information transfer (EXIT) charts, it is shown that the proposed technique provides an exceptionally good error performance. In particular, both EXIT chart analysis and simulation results indicate that a turbo pinch-off and a bit error rate around 10-6happen at a signal-to-noise ratio that is well below the coded modulation and BICM capacities using traditional signal sets. For example, with code rates ranging from 2/3 to 7/8, the proposed system can operate 0.82 dB-2.93 dB lower than the BICM capacity with QPSK and Gray labeling. The mutual information gain offered by rotated constellations can be therefore utilized to design simple yet near Shannon limit systems in the high-rate regions.

This paper studies the mutual information improvement attained by rotated multidimensional (multi-D) constellations via a unitary precoder G ∈ CN×Nin Rayleigh fading. At first, based on the symmetric cut-off rate of the N-D signal space, we develop a design criterion with regard to the precoder G. It is then demonstrated that the use of rotated constellations in only a reasonably low dimensional signal space can significantly increase the mutual information in high-rate regimes. By considering the QPSK system, we then propose a class of good unitary rotation G in 4-D signal space using parameterization approach, which are shown to provide remarkable improvement. To further illustrate the potential of multi-D constellation and to show the practical use of mutual information improvement, we propose a simple yet powerful coded modulation scheme in which a (multi-D) mapping technique employed in a multi-D rotated constellation is concatenated with a short-memory high-rate convolutional code (CC). By using extrinsic information transfer (EXIT) charts, it is demonstrated that the proposed technique provides an exceptionally good error performance. For example, by using the derived 4×4 rotation, together with QPSK constellation, and a simple rate-3/4 outer convolutional code, it is shown that the proposed system can operate 1.39 dB lower than the traditional coded modulation capacity at the bit error rate (BER) level around 10-6.

A comprehensive performance analysis of the energy detector over fading channels with single antenna reception or with antenna diversity reception is developed. For the no-diversity case and for the maximal ratio combining (MRC) diversity case, with either Nakagami-m or Rician fading, expressions for the probability of detection are derived by using the moment generating function (MGF) method and probability density function (PDF) method. The former, which avoids some difficulties of the latter, uses a contour integral representation of the Marcum-Q function. For the equal gain combining (EGC) diversity case, with Nakagami-m fading, expressions for the probability of detection are derived for the cases L =2,3,4 and L >; 4, where L is the number of diversity branches. For the selection combining (SC) diversity, with Nakagami-m fading, expressions for the probability of detection are derived for the cases L =2 and L >; 2. A discussion on the comparison between MGF and PDF methods is presented. We also derive several series truncation error bounds that allow series termination with a finite number of terms for a given figure of accuracy. These results help quantify and understand the achievable improvement in the energy detector's performance with diversity reception. Numerical and simulation results are also provided.

The cooperation among cognitive users (CUs) is considered as an efficient means to improve the primary user (PU) sensing in cognitive radio environment. Almost all previous related works employ the cooperation among CUs for PU activity detection whereas in this paper, the notions of cooperation among PUs and CUs are applied. This is achieved by allocating the available PU power among OFDMA subcarriers with two objectives 1. Guaranteed spectral efficiency to PU 2. Maximize detection of PU presence to a CU. The dynamic nature of channel parameters significantly improves the detection probability of CU with a minor reduction in PU's spectral efficiency. Analysis shows that a reduction of 5% spectral efficiency could be utilized to gain more than 15% in terms of the correct detection probability. The convexity of the formulated problem is analyzed. Finally, we propose deploying our scheme with CU collaborative sensing schemes to improve the detection probability in the low signal-to-noise ratio regions.

This paper addresses the problem of energy detection of unknown deterministic signal of a primary user in a cognitive radio environment. As an extension to the previous works, we focus on equal gain combining technique when the wireless channel is modeled as Nakagami-m. We derive series form exact expressions for probability of detection and false alarm when the number of diversity branches are 1, 2, 3 and L ges 4. Finally, performance variation is shown against the number of diversity branches and the time bandwidth product in decision statistic with the aid of numerical results.