This paper studies the transmission of progressive images over multiple-input multiple-output (MIMO) channels with inter-cell interference. For the transmission of progressive images, the optimization of jointly allocating various spectral efficiencies and spatial multiplexing rates to a series of numerous packets has been a challenging problem. In addition, if transmit power control is also involved with the optimization for interference channels, the problem becomes more complicated. To address such issues, in this paper, a neural network based optimization method is proposed, where the input layer of the network takes the distortion-rate characteristics of progressive images and the estimates of channel propagation gains between transmitters and receivers. Unsupervised learning is adopted to train the network, where the softmax activation functions of the output layer are exploited to average the expected distortions of the images over the predicted probability distributions of spectral efficiencies and spatial multiplexing rates. The proposed scheme offers significantly improved performance, compared to the baseline method that separately optimizes transmit power and a set of spectral efficiencies and spatial multiplexing rates. It is demonstrated that a neural network is able to analyze and learn the highly nonlinear distortion-rate characteristics of images that are associated with MIMO channel fading effects in the presence of inter-cell interference.

In this paper, we consider the transmission of embedded (or progressive) images over interference channels for the purposes such as surveillance, and special missions of public safety or emergencies. When transmitting embedded images, the joint optimization of source and channel coding for a series of numerous packets has been a challenging problem. Further, the problem is more complicated if the interference is present and the relevant transmit signal power control is also involved with the optimization. This is because the number of ways of jointly optimizing transmit power and a set of channel codes to be assigned to progressive packets is much larger than that of solely optimizing a set of channel codes. For a single communication link, there have been many studies about the optimal allocation of channel codes to progressive packets, but those studies do not provide a solution for the aforementioned optimization problem. We propose a neural network based optimization method to address such issues in interference channels. Specifically, the proposed scheme incorporates a fully-connected layer based neural network, where the input layer takes the distortion-rate characteristics of images to be transmitted, and the estimate of channel propagation effects such as path loss and shadow fading. Then, the network predicts the optimal transmit power and a set of optimal channel codes to be assigned to progressive packets. We demonstrate that a neural network can analyze and learn the highly nonlinear distortion-rate characteristics of images, which are associated with wireless channel fading effects, and can com up with the relevant optimization strategy. Compared to the baseline method that separately optimizes transmit power and a set of channel codes, our scheme offers significantly improved peak-signal-to-noise ratio performance.

This paper considers unmanned aerial vehicles (e.g., drones and quadcopters) that accomplish missions of transmitting a large number of progressive images over air-to-ground multiple-input multiple-output (MIMO) links for surveillance applications, and special missions of public safety or emergencies. For the transmission of progressive images, the joint optimization of source and channel coding of a series of numerous packets has been a challenging problem. Further, the problem is more complicated if the space-time coding is also involved with the optimization in a MIMO system. This is because the number of ways of jointly assigning channel codes and space-time codes to progressive packets is much larger than that of solely assigning channel codes to the packets. Recently, Chang et al. applied a parametric approach to address such a problem, and proposed an optimization algorithm that exponentially reduces the computational complexities of the conventional exhaustive search. For resource-constrained aerial equipments, complexity is of particular importance due to hardware power consumption and size issues. To address such issues, we propose a neural network-based optimization method to further reduce computational complexities. We demonstrate that the nonlinear distortion-rate characteristics of the images, which are combined with wireless channel fading effects, can be analyzed and learned by a neural network. It is shown that compared to the algorithm proposed by Chang et al., our approach significantly reduces the computational complexities, while offering nearly identical peak-signal-to-noise ratio (PSNR) performances.

The optimization of joint source and channel coding for a sequence of numerous progressive packets has been a challenging problem. Further, the problem becomes more complicated if the space-time coding is also involved with the optimization in a multiple-input multiple-output (MIMO) system. This is because the number of ways of jointly assigning channel codes and space-time codes to progressive packets is much larger than that of solely assigning channel codes to the packets. To our knowledge, there is no complete and feasible solution for the optimization of joint source, channel, and space-time coding of progressive packets. This paper applies a parametric approach to address such a highly nonlinear optimization problem in MIMO systems. We use the parametric methodology and derive some relevant properties, which are exploited to propose an efficient optimization method where the joint assignment of channel codes and space-time codes to the packets can be optimized in a packet-by-packet manner. As a result, the computational complexity of the proposed method linearly increases in the number of packets, whereas that of the exhaustive search exponentially increases in the number of packets. The numerical results show that the proposed method significantly improves the peak-signal-to-noise ratio performance of the conventional rate-based optimal solution in a MIMO system.

This paper considers a multimedia broadcasting scenario in which two types of heterogeneous users with different display resolutions and different numbers of antennas stay in the service area. We propose an image broadcasting scheme that uses the image super-resolution (SR) techniques, spatial diversity, and diversity-multiplexing tradeoff (DMT) achieving codes. The proposed scheme broadcasts a low-resolution (LR) image to two types of users, along with residual pixel-error map containing high-frequency details of high-resolution (HR) image. Then, a user retaining an HR screen employs SR to reconstruct an HR image from the received LR image, and exploits the residual map to further enhance the image quality. Our scheme properly trains the neural network models of the deep learning-based SR by taking into account the source coding rates of the images. Considering the relationship between the number of antennas and screen resolution, based on hardware space of user devices, the proposed scheme encodes an LR image with spatial diversity, and encodes residual map with DMT-achieving codes. Numerical evaluation shows that our scheme significantly outperforms the baseline strategy that broadcasts either HR or LR images.

The distance threshold, which is used to distinguish the cell-edge region from the cell- center region, is an important factor in fractional frequency reuse (FFR) system performance. In this paper, we study the optimal distance threshold to maximize system throughput in the downlink cellular networks including aerial base stations. Subject to the constraint that a given target outage probability is satisfied, the optimal distance threshold is analyzed as a function of cell size. It is proven that when the sizes of all cells in the network are scaled at the same rate, the optimal distance threshold normalized by cell size is non-decreasing in the cell size. The analytical results in this paper provide a system design guideline for initial planning of FFR cellular networks of different sizes including macro, pico, and femto systems. In particular, for size-scalable aerial networks comprising base stations in the sky, such as balloons or unmanned aerial vehicles, our analysis offers insight into the design of the distance threshold with regard to cell size.

A fractional frequency reuse (FFR) system is an inter-cell interference coordination scheme used in cellular networks. In FFR systems, the available bandwidth is partitioned into orthogonal subbands such that the users near the cell center adopt subbands of a frequency reuse (FR) factor equal to one (i.e., Full FR), and the users near the cell edge adopt the subbands of an FR factor greater than one (i.e., Partial FR). The proper design of Full FR coverage, which is used to distinguish Full FR regions from Partial FR regions, plays a critical role in FFR system performance. This paper studies the optimal Full FR coverage that maximizes system throughput in the downlink in multiple-input multiple-output (MIMO) cellular networks. For MIMO systems, orthogonal space-time block codes are considered. We analytically compare the outage probabilities of Full FR and Partial FR for a given user's location, where the outage probability is evaluated through small-scale multipath fading. By doing so, subject to the constraint that a given target outage probability (quality-of-service) is satisfied, the optimal Full FR coverage is analyzed as a function of base station (BS) power. We prove that the optimal Full FR coverage is a non-increasing function of BS power when the powers of all BSs in the network are scaled up or down at the same rate. This result offers insight into the design of Full FR coverage in relation to BS power; we gain insight into the complicated relationship between crucial FFR design parameters.

The optimization of joint source and channel coding for a sequence of numerous progressive packets is a challenging problem. Further, the problem becomes more complicated if the space- time coding is also involved with the optimization in a multiple-input multiple-output (MIMO) system. This is because the number of ways of jointly assigning channel codes and space-time codes to progressive packets is much larger than that of solely assigning channel codes to the packets. This paper applies a parametric approach to address that complex joint optimization problem in a MIMO system. Employing the parametric distortion-rate function, the joint assignment of channel codes and space-time codes to the packets can be optimized in a packet-by- packet manner. As a result, the computational complexity of the optimization is exponentially reduced, compared to the exhaustive search. The numerical results show that the proposed method significantly improves the peak-signal-to-noise ratio performance of the rate-based optimal solution in a MIMO system.

In this study, the performance of a dual‐hop amplify‐and‐forward relaying system with beamforming is analysed, where only the source and destination are equipped with multiple antennas and both hops are subject to κ – μ fading channels. The κ – μ fading model is a general fading model that can accurately model practical small scale fading in line‐of‐sight environments and accommodates Rician, Nakagami‐ m , and Rayleigh as special cases. New exact analytical expressions on the outage probability (OP), average symbol error rate (SER), and average capacity are derived. Moreover, asymptotic results for the OP, SER, and average capacity are also derived in simpler forms in terms of basic elementary functions which make it easy to understand the system behaviour and the impact of the channel parameters. These analytical results are general and can emulate different symmetric and asymmetric fading scenarios as special cases such as Rician/Rician, Nakagami‐ m /Nakagami‐ m , Rayleigh/Rayleigh, and mixed κ – μ , Rician, Nakagami‐ m , and Rayleigh fading links.

This paper studies the optimal frequency reuse for the transmission of multimedia scalable sources, such as embedded images or scalable video, which need unequal error protection or unequal transmission rates in the bitstream. First, we analyze the crossover of the outage probabilities for full and partial frequency reuse cases in terms of the data rate. We prove that we can find a crossover of the outage probability curves for a data rate lower than a given threshold, which is a function of the parameters such as the partial frequency reuse factor and the user location in the cell. Moreover, the crossover point in the signal-to-noise ratio (SNR) is a strictly increasing function of the data rate. On the other hand, for a data rate higher than or equal to the threshold, there is no crossover; for all SNRs, the outage probability of full-frequency reuse is lower than that of partial-frequency reuse. The results are proven for the arbitrary location of a user in a cell, and for an arbitrary partial frequency reuse factor. Furthermore, the results hold, regardless of the numbers of transmit and receive antennas in the multiple-input multiple-output systems of orthogonal space-time block codes, and of the vertical Bell Labs space-time architecture with a zero-forcing linear receiver. Based on the analysis, we propose unequal-frequency reuse for the optimal transmission of scalable sources. The numerical results show that the peak-SNR performance improves when a sequence of scalable packets is transmitted at the subbands governed by unequal-frequency reuse in cellular networks.

The advanced multibeam satellite equipped with phased array antenna and solid state power amplifiers can generate flexible beams, by managing interbeam interference to serve a very large number of users effectively over its coverage area. Onboard processing (OBP) functionality can enhance the flexibility of a large-scale antenna by speeding up computational processes and saving precious radio link spectrum. In this paper, we derive a cross-layer OBP design of switching/routing, beamforming, and user scheduling as taking advantage of fine spatial resolution capability of phased array antenna satellites. We evaluate tradeoff between OBP computational complexity and throughput performance, showing that the additional complexity of an increased number of switch ports and phased array antenna gain patterning is compensated by high throughput gain achieved by mitigating interference. Our analysis shows that throughput gain for the next generation satellite system can be as high as 40, compared with the conventional multiple beam antenna with travelling wave tube amplifiers, and that beamforming is critical for achieving high spectral efficiency in the crowded service area. We then investigate the impacts of onboard switching and phased array antenna beamforming to practical routing protocols, such as open short path first and routing information protocol.

In this paper, the performance of a dual-hop variable-gain amplify-and-forward (AF) relay system with beamforming is analyzed for the recently proposed κ-μ shadowed fading model. The κ - μ shadowed fading model can emulate different types of empirical wireless channels that undergo shadowing, fading, or both and it includes the κ-μ, Rayleigh, Nakagami-m, Rician, and Rician shadowed channels as special cases. We consider that the source and destination are equipped with multiple-antennas and communication occurs through a single-antenna variable-gain relay. First, we derive the new exact analytical expressions for the outage probability (OP) and average capacity, then, we derive the asymptotic results for the OP and average capacity in terms of basic elementary functions to get useful intuition on the impact of the shaping parameters and multiple-antennas on the system performance. These results enable us to explicitly analyze the performance of relaying system under different environments arising from fading and shadowing occurring simultaneously as well as separately. Our results are general so as to be readily reduced to previously published results for classical fading channels as well as new additional ones.

In a previous paper, Chang et al. presented a method for iterative decoding of FEC-based multiple description codes in image transmission. In this correspondence, we clarify that an outer interleaver used in the above research was previously proposed for the iterative decoding and optimization of product codes in image transmission.

Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.

With progressive image or scalable video encoders, as more bits are received, the source can be reconstructed with progressively better quality. These progressive codes have gradual differences of importance in their bitstreams, which necessitates multiple levels of unequal error protection (UEP). One practical method of achieving UEP is based on a constellation of nonuniformly spaced signal points, or hierarchical constellations. However, hierarchical modulation can achieve only a limited number of UEP levels for a given constellation size. Though hierarchical modulation has been intensively studied for digital broadcasting or multimedia transmission, most work has considered only two layered source coding, and methods of achieving a large number of UEP levels for progressive transmission have rarely been studied. In this paper, we propose a multilevel UEP system using multiplexed hierarchical quadrature amplitude modulation (QAM). We show that multiple levels of UEP are achieved by the proposed multiplexing method. When the BER is dominated by the minimum Euclidian distance, we derive an optimal multiplexing approach which minimizes both the average and peak powers. We next propose an asymmetric hierarchical QAM which reduces the peak-to-average power ratio (PAPR) of the proposed UEP system without any performance loss. Numerical results show that the performance of progressive transmission over Rayleigh fading channels is significantly enhanced by the proposed methods.

We study single-term exponential-type bounds (also known as Chernoff-type bounds) on the Gaussian error function. This type of bound is analytically the simplest such that the performance metrics in most fading channel models can be expressed in a concise closed form. We derive the conditions for a general single-term exponential function to be an upper or lower bound on the Gaussian error function. We prove that there exists no tighter single-term exponential upper bound beyond the Chernoff bound employing a factor of one-half. Regarding the lower bound, we prove that the single-term exponential lower bound of this letter outperforms previous work. Numerical results show that the tightness of our lower bound is comparable to that of previous work employing eight exponential terms.

We propose superposition multiple-input multiple-output (MIMO) coding for the transmission of unequally important sources in a point-to-multipoint system. First, a tradeoff between Alamouti code and spatial multiplexing (V-BLAST) is analyzed in terms of the average bit error rate (BER), where the maximum data rates of both MIMO schemes are set to be equal. The results show that for a given target bit error rate, Alamouti code is preferable for a low data rate, and spatial multiplexing is preferable for a high data rate. For layered sources such as scalable video, the more important component typically has lower data rate than does the less important component. Based on these, we construct a superposition MIMO scheme where two different MIMO techniques are hierarchically combined such that important data is Alamouti coded, less important data is spatially multiplexed, and then two unequally important data symbols are superposed.

Recently, multiple description source coding has emerged as an attractive framework for robust multimedia transmission over packet erasure channels. In this paper, we mathematically analyze the performance of n-channel symmetric FEC-based multiple description coding for a progressive mode of transmission over orthogonal frequency division multiplexing (OFDM) networks in a frequency-selective slowly-varying Rayleigh faded environment. We derive the expressions for the bounds of the throughput and distortion performance of the system in an explicit closed form, whereas the exact performance is given by an expression in the form of a single integration. Based on this analysis, the performance of the system can be numerically evaluated. Our results show that at high SNR, the multiple description encoder does not need to fine-tune the optimization parameters of the system due to the correlated nature of the subcarriers. It is also shown that, despite the bursty nature of the errors in a slow fading environment, FEC-based multiple description coding without temporal coding provides a greater advantage for smaller description sizes.

Progressive image and scalable video have gradual differences of importance in their bitstreams, which can benefit from multiple levels of unequal error protection (UEP). Though hierarchical modulation has been intensively studied as an UEP approach for digital broadcasting and multimedia transmission, methods of achieving a large number of UEP levels have rarely been studied. In this paper, we propose a multilevel UEP system using multiplexed hierarchical quadrature amplitude modulation (QAM) for progressive transmission over mobile radio channels. We suggest a specific way of multiplexing, and prove that multiple levels of UEP are achieved by the suggested method. When the BER is dominated by the minimum Euclidian distance, we derive an optimal multiplexing approach which minimizes both the average and peak powers. An asymmetric hierarchical QAM which reduces the peak-to-average power ratio (PAPR) without performance loss is also proposed. Numerical results show that the performance of progressive transmission over Rayleigh fading channels is significantly enhanced by the proposed UEP systems.