An Insight about Current Research Ideas in Wireless Communication-A Review

In the telecommunications sector, wireless industry has proliferated its growth to such an extent that everyone in the world is a user of some form of developing technology. Wireless communications is one of the most celebrated engineering success stories for the past two decades that has radically changed the life of people. This paper provides a very broad technical view of current research ideas in wireless communication field, emphasizing on the most relevant design applications that could be utilized efficiently. A wide coverage in the areas of research like cognitive radios, opportunistic spectrum sensing, Multiple Input Multiple Output(MIMO) relay networks, technical overview for wireless ad hoc networks, research issues in wireless sensor networks and ultra wideband communications(UWB) is summarized in this paper. KeywordsMIMO, UWB, Ad hoc, cognitive radios 1. RESEARCH ISSUES IN COGNITIVE RADIOS The basic conception of software-defined radio (SDR) initiated in the early 1990s, and has now it has become an important core technology for future generation wireless communications. In 1997, the U.S. DoD recommended replacing its 200 families of radio systems with a single family of SDRs in the programmable modular communications system (PMCS) guideline document [1]. The ultimate objective of SDR is to configure a radio platform like a freely programmable computer so that it can adapt to any typical air interface by using an appropriate kind of programming interface. SDR is targeted to implement all kinds of air interfaces and signal processing functions using software in one device. Some of the research ideas in Cognitive radios are listed below. 1.1 MODULATION AND PRIMARY USE RECOGNITION The main research analysis here concentrates on radio signal analysis, modulation recognition and bit stream analysis which are applied to identify whether an alarm corresponds to a primary user, or a secondary user, or noise (false alarm). Modulation recognition is an intermediate step between signal detection and demodulation. Knowledge of the types of the service operating on a channel in a way minimizes overhead to the cognitive radio and its impact on the primary users of the spectrum. A cognitive radio should be able to recognize other cognitive radios on the link channel to prevent them sensing one another as primary users and jumping channels. Modulation recognition can be likelihoodbased or feature based [2]. The former is based on the likelihood function of the received signal and the decision is made by comparing the likelihood ratio against a threshold. The likelihood-based algorithms are optimal in the Bayesian sense, they minimize the probability of false classification, but suffer from high computational complexity [33]. The feature-based approach makes decisions based on the observed values of typically, several features. In general, modulation recognition is a challenging task, especially in a non cooperative environment, where no prior knowledge of the incoming signal is available. 1.2 MANAGEMENT OF THE AVAILABLE SPECTRUM Spectrum management functions address four main challenges: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. Spectrum mobility allows a cognitive radio to exchange its frequency of operation in a dynamic manner by allowing the cognitive radios to operate in the best available frequency band seamlessly [22-24]. Spectrum sharing deals with fair spectrum scheduling, which is medium access control MAC functionality. A cognitive radio needs to maintain an up-to-date list of available channels within a band. The channel usage database can also be used to avoid the occupied licensed channels, and a secondary user estimates its position and checks a database to find out which channels are vacant in its vicinity. 1.3 ERASURE CORRECTION CODES A secondary user selects a set of sub channels from the primary user band to establish a secondary user link that adapts itself in accordance with the primary user spectral diversity on that band. The secondary user is required to vacate a sub channel as soon as a primary user becomes active on that sub channel. In order to compensate for this loss, a class of erasure correction codes called LT (Luby Transform) codes or Fountain codes [3] can be used for packet-based channels with erasures before transmitting secondary user packets on these sub channels. This provides packet-level protection at the transport layer or higher, augmenting the bit-level protection that may be provided by the MAC and physical layers. P.Sunil Kumar et al./ International Journal of Computer Science & Engineering Technology (IJCSET) ISSN : 2229-3345 Vol. 4 No. 05 May 2013 497 1.4 AWARENESS OF AVAILABLE SPECTRUM Spectrum awareness over an entire operating bandwidth of interest is a preliminary and very crucial task of a cognitive radio. The sensitivity of cognitive radio is necessary to outperform the primary user receiver by a large margin in order to escape from the hidden terminal problem [18]. This makes spectrum sensing, or spectrum awareness, a very challenging research problem. For cognitive radios, a cross-layer design approach is desirable since the process delay is required to be very minimum. Spectrum awareness can be either passive or active awareness. In passive awareness, the spectrum use pattern is obtained not by sensing with the secondary system itself, but by negotiating with primary users, or from a server or database. The passive awareness approach results in considerable signalling for distribution of frequency information [29]. In active awareness, the secondary user actively senses the frequency spectrum to obtain the spectrum use pattern. Active spectrum awareness can be performed in a non cooperative or cooperative manner. Cooperation helps to cope with the hidden problem. Active spectrum awareness can be either reactive or proactive, depending on how white spaces (unused frequency bands) are searched. Reactive schemes operate on an on-demand basis, where a cognitive radio starts to sense the spectrum only when it has data to send. Proactive schemes, on the other hand, minimize the delay of secondary users by finding an idle band through maintaining a list of licensed bands currently available for opportunistic access through periodic spectrum sensing. 2. RESEARCH ISSUES IN MIMO RELAY NETWORKS Virtual MIMO schemes can be used to improve communication performance of wireless adhoc networks. Virtual MIMO is a network-based approach. Different nodes in the network can act as elements of an antenna array. As the array elements are not physically connected, a large amount of information must be sent to the combining nodes. In this approach, multiple individual single-antenna nodes cooperate for energy-efficient communications. Examples of virtual MIMO schemes are an Alamouti-encoded scheme for single-hop transmissions[4], a STBC-encoded scheme without perfect synchronization[5], and a clustered topology-based, time-division, DF multirelay, space-time coded MIMO channel for multihop transmissions[6]. 2.1 CLUSTERED RELAYING ISSUES A wireless network with fading and a single source-destination pair is considered in an ideal scenario [7]. The information reaches the destination via multiple hops through a sequence of layers of single-antenna relays. Each layer of relays can be treated as virtual MIMO. At high SNR, AF is optimal in terms of degrees of freedom, as it achieves the degrees of freedom equal to that of a point-topoint MIMO system. Hence, lack of coordination in relay nodes does not reduce the achievable degrees of freedom. The performance of this AF strategy degrades with increasing network size. This phenomenon is analysed by finding the tradeoff between network size, rate, and diversity. A cluster-based cooperative strategy using incremental redundancy cooperative coding for slow Rayleigh Fading is also proposed [8]. 2.2 DISTRIBUTED STBCs Distributed space-time coding achieves cooperative diversity without CSI at the relays. Using this scheme, antennas of the distributive relays work as transmit antennas of the sender and generate a space-time code at the receiver. It achieves the maximal diversity when the transmit power is infinitely large. Orthogonal STBCs (OSTBCs) are particularly suitable for transmission in the network setting using distributed space-time coding, where each node transmits a different column of the OSTBC matrix [9]. Distributed space-time coding achieves higher diversity always using the same orthogonal designs, when there is more than one relay [10]. Distributed STBCs are designed for wireless networks that have a large set of single-antenna relay nodes, but only a small, a priori unknown subset of nodes is active at any given time [11]. The signal transmitted by an active relay node is the product of an information-carrying code matrix and a unique node signature vector of length Nc. This approach allows convenient exploitation of existing coherent, differential, and non-coherent STBCs originally designed for Nc co-located antennas, and accordingly allows for low-complexity coherent, differential, and non coherent detection. Existing STBCs designed for Nc>2 are co-located antennas which is the most favourable choice for the code matrix, guaranteeing a diversity order of d=min {Ns, Nc} in case of Ns active nodes. 2.3 TRANSMITTER AND RECEIVER COOPERATIONS In [12], capacity improvement from transmitter and receiver cooperation is investigated in a two-receiver network with phase fading and full CSI available at all nodes. The transmitters cooperate by first exchanging messages over an orthogonal transmitter cooperation channel, then encoding jointly with dirty-paper coding [35]. The receivers cooperate by using Wyner-Ziv CF over an analogous orthogonal receiver cooperation channel. Transmitter cooperation outperforms receiver cooperation and improves capacity over non cooperative transmission under most op