Continuous Phase Modulation–Direct Sequence Spread Spectrum (CPM-DSSS) is a promising scheme for a secured Point-to-Point (P2P) communication system having Anti-Jamming (AJ) capabilities. However, like other communication systems, synchronization of CPM-DSSS based systems is required for reliable detection of data. This paper presents a novel algorithm for estimating the timing and phase offset for binary full-response CPM-DSSS based systems. A burst mode transmission is considered here, and within each burst, a training sequence is embedded along with data. Firstly, the entire burst is spread using DSSS and then modulated with CPM, which is later upconverted and passed on to the channel. After down-conversion at the receiver, the proposed algorithm estimates timing and phase offset from the received spread training sequence. Then estimation accuracy of the proposed algorithm is compared with the state-of-the-art. The results indicate that the proposed joint estimator is superior by 9 dB and 10 dB for the estimation of timing and phase offset, respectively, as compared to the existing algorithm. Furthermore, the estimator’s variance for three different frequency pulses is compared with Modified Cramer-Rao Bound (MCRB). The results suggest that the phase offset estimator’s variance approaches MCRB for all Signal-to-Noise Ratios (SNRs). The effectiveness of the proposed algorithm in the multipath fading channel is also demonstrated.

The advancement and spread of the internet-of-things (IoT) have massively been increased over a decade. With the widespread of IoT networks, it is becoming difficult to acquire and execute real-time data. Network function virtualization (NFV) provides a flexible and efficient solution for IoT-based applications and service management. NFV creates a virtualized environment that can run a large number of micro-services for different IoT applications by using the virtual network functions (VNFs) through placement and chaining. In this paper, we propose a novel fuzzy inference-based placement and migration (FIPAM) approach for placement and migration/chaining of VNFs to ensure that resource allocation is carefully carried out during VNF orchestration and embedding. Firstly, we formulate the VNF chaining and placement problem. Secondly, we propose a lightweight VNF placement solution that considers the underlying network conditions while making the placement decisions. A novel usage of fuzzy inference is proposed to optimize the chaining mechanism along with the dynamic instantiation of VNFs to meet specific service needs. Simulation results are shown to validate the superiority of the proposed algorithm over existing schemes.

Tactical software defined radio (SDR) networks demand stringent requirements of latency, throughput, and reliability. In the past, significant efforts have been made to achieve maximal efficiency with modifications and improvements either in an individual layer or through the cross-layer design of its working protocol. In this paper, we propose a novel cross-layer design consisting of adaptive multi-input medium access control (AMI-MAC) layer along with an intelligent channel allocation scheme supported by a multiband multimode physical layer. A cognitive engine further empowers this cross-layer design approach to achieve high throughput, improved quality of service (QoS), and adaptive range capabilities. The proposed physical layer exhibits a mixed use of narrowband and wideband waveforms accommodating different range requirements as per demanded QoS. The uniqueness of the proposed physical layer enables SDR to operate in hybrid topology by receiving multiple narrowband signals of different bandwidths with the same configuration of wideband RF front end. The proposed AMI-MAC design ensures a reduction in both control and data phase latency. MAC layer ensures the maximal utilization of the time and frequency spectrum. Bandwidth and delay optimization is also managed by the proposed trio of the physical layer, MAC, and cognition to reduce latency and achieve desired QoS. Simulation results are presented to show the superiority of the proposed design over conventional tactical radio MAC.