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Millimeter wave (mmWave) communications have been considered as a key technology for future 5G wireless networks since it can provide orders-of-magnitude wider bandwidth than current cellular bands. In order to overcome the severe propagation loss of mmWave channel, economic and energy-efficient analog/digital hybrid precoding and combining transceiver architecture is widely used in mmWave massive multiple-input multiple-output (MIMO) systems. The large scale analog precoder/combiner can implement beamforming and generate significant beamforming gain while the digital precoding/combining layer offers sufficient freedom and enables multi-stream/multi-user transmission. The major challenge in designing hybrid precoder is the practical constraints of the analog precoder, such as constant modulus, which is usually imposed by phase shifters. Thus, the hybrid precoder design is deemed as solving various matrix factorization problems with constant modulus constraints of the analog precoder.
The broadcast nature of the wireless medium makes wireless networks ubiquitously accessible and inherently non-secure. An eavesdropper within range of a wireless transmission may intercept the transmitted signal while staying undetected. Commonly used security methods rely on cryptographic (encryption) and steganographic (covert communication) means employed at upper layers of the wireless network. It is still highly desirable, however, to enhance the core security of wireless communications by reducing the likelihood that propagating signals are intercepted by eavesdroppers in the first place. As a result, there has been growing interest recently in the development of physical layer security mechanisms for the wireless link.
Digital data embedding in digital media is an information technology field of rapidly growing commercial as well as national security interest. Applications may vary from annotation, copyright-marking, and watermarking, to single-stream media merging (text, audio, image) and covert communication. In annotation, secondary data are embedded into digital multimedia to provide a way to deliver side information for various purposes; copyright-marking may act as permanent “iron branding” to show ownership; fragile watermarking may be intended to detect future tampering; hidden low-probability-to-detect (LPD) watermarking may serve as identification for confidential data validation or digital fingerprinting for tracing purposes. Covert communication or steganography, which literally means “covered writing” in Greek, is the process of hiding data under a cover medium (also referred to as host), such as image, video, or audio, to establish secret communication between trusting parties and conceal the existence of embedded data.
Compressed sensing (CS), also referred to as compressive sampling, is an emerging body of work that deals with sub- Nyquist sampling of sparse signals of interest. Rather than collecting an entire Nyquist ensemble of signal samples, CS can reconstruct sparse signals from a small number of (random or deterministic) linear measurements via convex optimization, linear regression, or greedy recovery algorithms. In this paper, we considered a video transmission system where the transmitter or encoder performs nothing more than compressed sensing acquisition without the benefits of the familiar sophisticated forms of video encoding. Such a setup may be of particular interest, e.g., in problems that involve large wireless multimedia networks of primitive lowcomplexity, low-cost video sensors. We proposed a new sparsity-aware video decoding algorithm for compressive video streaming systems to exploit long-term interframe similarities and pursue the most efficient and effective utilization of all available measurements.
With the rapid proliferation of a variety of consumer oriented wireless devices, demand for access to radio spectrum has been growing dramatically and the limited available spectrum is becoming increasingly congested. At the same time, location-dependent bands of pre-licensed radio spectrum may experience low utilization. Cognitive radio (CR) is an emerging technology aiming at improving spectrum utilization efficiency by allowing secondary users/networks to opportunistically share radio spectrum originally licensed by primary users/networks without causing “harmful” interference to them.
In code-division multiplexing (CDM) systems, individual users/signals use distinct signatures (spreading codes) to access a common, in time and frequency, communication channel. In conjunction with channel and receiver design specifics, the overall system performance is determined by the selection of the user signature set. Signature set metrics of interest include the total squared correlation (TSC), maximum squared correlation (MSC), total asymptotic efficiency (TAE), sum capacity, etc.
Direct-sequence code division-multiple-access (DS-CDMA) is one of the most common multiple-access techniques for wireless communication systems. In recent decade, various kinds of receivers have been developed for DS-CDMA systems. Almost all these receivers require knowledge of the users’ spreading sequences (signatures). Here, we aim to blindly extract the information data symbols of all participating DS-CDMA users without knowledge of their spreading sequences nor channel state information and in the absence of any pilot signal (training sequence).