Peak to average power ratio based spatial spectrum sensing for cognitive radio systems

The recent convergence of wireless standards for incorporation of spatial dimension in wireless systems has made spatial spectrum sensing based on Peak to Average Power Ratio (PAPR) of the received signal, a promising approach. This added dimension is principally exploited for stream multiplexing, user multiplexing and spatial diversity. Considering such a wireless environment for primary users, we propose an algorithm for spectrum sensing by secondary users which are also equipped with multiple antennas. The proposed spatial spectrum sensing algorithm is based on the PAPR of the spatially received signals. Simulation results show the improved performance once the information regarding spatial diversity of the primary users is incorporated in the proposed algorithm. Moreover, through simulations a better performance is achieved by using different diversity schemes and different parameters like sensing time and scanning interval

Performance of smart antennas with receive diversity in wireless sensor networks

In this paper we propose a Geometrically Based Single Bounce Elliptical Model (GBSBEM) for multipath components involving randomly placed scatterers in the scattering region with sensors deployed on a field. The system model assumes a cluster based wireless sensor network (WSN) which collects information from the sensors, filters and modulates the data and transmit it through a wireless channel to be collected at the receiver. We first develop a GBSBE model and based on this model we develop our channel model. Use of Smart antenna system at the receiver end, which exploits various receive diversity combining techniques like Maximal Ratio Combining (MRC), Equal Gain Combining (EGC), and Selection Combining (SC), adds novelty to this system. The performance of these techniques have been proved through matlab simulations and further ahead based on different number of antenna elements present at the receiver array, we calculate the performance of our system in terms of bit-error-rate (BER). Based on the transmission power we quantify for the energy efficiency of our communication model.<br /

Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer

This paper studies a wireless-energy-transfer (WET) enabled massive multiple-input-multiple-output (MIMO) system (MM) consisting of a hybrid data-and-energy access point (H-AP) and multiple single-antenna users. In the WET-MM system, the H-AP is equipped with a large number $M$ of antennas and functions like a conventional AP in receiving data from users, but additionally supplies wireless power to the users. We consider frame-based transmissions. Each frame is divided into three phases: the uplink channel estimation (CE) phase, the downlink WET phase, as well as the uplink wireless information transmission (WIT) phase. Firstly, users use a fraction of the previously harvested energy to send pilots, while the H-AP estimates the uplink channels and obtains the downlink channels by exploiting channel reciprocity. Next, the H-AP utilizes the channel estimates just obtained to transfer wireless energy to all users in the downlink via energy beamforming. Finally, the users use a portion of the harvested energy to send data to the H-AP simultaneously in the uplink (reserving some harvested energy for sending pilots in the next frame). To optimize the throughput and ensure rate fairness, we consider the problem of maximizing the minimum rate among all users. In the large-$M$ regime, we obtain the asymptotically optimal solutions and some interesting insights for the optimal design of WET-MM system. We define a metric, namely, the massive MIMO degree-of-rate-gain (MM-DoRG), as the asymptotic UL rate normalized by $\log(M)$. We show that the proposed WET-MM system is optimal in terms of MM-DoRG, i.e., it achieves the same MM-DoRG as the case with ideal CE.Comment: 15 double-column pages, 6 figures, 1 table, to appear in IEEE JSAC in February 2015, special issue on wireless communications powered by energy harvesting and wireless energy transfe

Performance of Transmit Antenna Selection in Multiple Input Multiple Output-Orthogonal Space Time Block Code (MIMO-OSTBC) System Joint with Bose-Chaudhuri-Hocquenghem (BCH)-Turbo Code (TC) in Rayleigh Fading Channel

To enhancing the performance of spatial modulation (SM) systems TAS (Transmit antenna selection) technique need to be essential. This TAS is an effective technique for reducing the Multiple Input Multiple Output (MIMO) systems computational difficulty and Bit error rate (BER) can increase remarkably by various TAS algorithms. But these selection methods cannot provide code gain, so it is essential to join the TAS with external code to obtain code gain advantages in BER. In some existing work, the improved BER has been perceived by joining Forward Error Correction Code (FEC) and Space Time Block Code (STBC) for MIMO systems provided greater code gain. A multiple TAS-OSTBC technique with new integration of Bose–Chaudhuri–Hocquenghem (BCH)-Turbo code (TC) is proposed in our paper. With external BCH code in sequence with the inner Turbo code, the TAS-OSTBC system is joining. This combination can provide increasing code gain and the effective advantages of the TAS-OSTBC system. To perform the system analysis Rayleigh channel is utilized. In the case with multiple TAS-OSTBC systems, better performance can provide by this new joint of the BCH-Turbo compared to the conventional Turbo code for the Rayleigh fading

POWER ALLOCATION ALGORITHM FOR MIMO BASED MULTI-HOP COOPERATIVE SENSOR NETWORK

Cooperative transmission is a new breed of wireless communication systems that enables the cooperating node in a wireless sensor network to share their radio resources by employing a distributed transmission and processing operation. This new technique offers substantial spatial diversity gains as the cooperating nodes help one another to send data over several independent paths to the destination node. In recent times, an extensive effort has been made to incorporate these systems in the future wireless networks like LTE (Long Term Evolution), IEEE 802.16j (Mobile Multi-hop Relay (MMR) Networks) and IEEE 802.16m (Mobile WiMAX Release 2 or WirelessMAN-Advanced). But, there are few technical issues which need to be addressed before this promising technique is integrated into future wireless networks. Among them, managing transmission power is a critical issue, which needs to be resolved to fully exploit the benefits of cooperative relaying. Optimal Power Allocation, is one such technique that optimally distributes the total transmission power between the source and relaying nodes thus saving a lot of power while maintaining the link quality. In the first part of the thesis, mathematical expressions of the received signals have been derived for different phases of cooperative transmission. Average-Bit-error-rate (ABER), has been taken as a performance metric to show the efficiency of cooperative relaying protocols. In the second part of this Chapter, a multi-hop framework has been presented for the power allocation algorithm with Amplify-and-Forward relaying protocol. The efficiency of the power allocation algorithm has been discussed with different scenarios i.e. First for a three node (2-Hop) wireless network configuration and then for a four node (3-Hop) wireless network configuration. The transmission scenarios (2-Hop and 3-Hop) have been further categorized into multiple cases on the basis of channel quality between source-to-destination, source-to-relay, relay-to-relay and relay-to-destination links.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format