Routing protocols in multi-hop cognitive radio networks (CRNs) can be classified into two main categories: local and global routing. Local routing protocols aim at decreasing the overhead of the routing process while exploring the route by choosing, in a greedy manner, one of the direct neighbors. On the contrary, global routing protocols choose the optimal route by exploring the whole network to the destination paying the flooding overhead cost. In this paper, we propose a primary user-aware$k$-hop routing scheme where$k$is the discovery radius. This scheme can be plugged into any CRN routing protocol to adapt, in real time, to network dynamics like the number and activity of primary users. The aim of this scheme is to cover the gap between local and global routing protocols for CRNs. It is based on balancing the routing overhead and the route optimality, in terms of primary users avoidance, according to a user-defined utility function. We analytically derive the optimal discovery radius ($k$) that achieves this target. Evaluations on NS2 with a side-by-side comparison with traditional CRNs protocols show that our scheme can achieve the user-defined balance between the route optimality, which in turn reflected on throughput and packet delivery ratio, and the routing overhead in real time.

We investigate dynamic content caching in relay networks where an intermediate relay station (RS) can adaptively cache data content based on their varying popularity. With the objective of minimizing the time average cost of content delivery, we formulate and study the problem of optimal RS cache allocation when the popularities of data content are unknown apriori to the network. While optimal dynamic cache control suffers the curse of dimensionality, we develop a fundamental lower bound on the achievable cost by any caching policy. Inspired by the structure of such lower bound, we develop a reduced-complexity policy that is shown numerically to perform close to the lower bound.

We investigate the performance of caching in relay networks where an intermediate relay station (RS) caches content for future demand by end users. With uncertain user demand over multiple data items and dynamically changing wireless links, we characterize the optimal transmission time for serving data items, cached data portion allocation of relay station and optimal service portion, which represents a part from the cached portion, to minimize the total average transmission energy. We argue that under several settings fully caching the higher popular items is the optimal caching policy which minimizes the total expected transmission energy.

We investigate the performance of dynamic proactive caching in relay networks where an intermediate relay station caches content for potential future use by end users. A central base station proactively controls the cache allocation such that cached content remains fresh for consumption for a limited number of time slots called proactive service window. With uncertain user demand over multiple data items and dynamically changing wireless links, we consider the optimal allocation of relay stations cache to minimize the time average expected service cost. We characterize a fundamental lower bound on the cost achieved by any proactive caching policy. Then we develop an asymptotically optimal caching policy that attains the lower bound as the proactive caching window size grows. Our analytical findings are supported with numerical simulations to demonstrate the efficiency of the proposed relay-caching.

We propose a primary user-aware k-hop routing scheme that can be plugged into any cognitive radio network routing protocol to adapt, in real time, to the environmental changes. The main use of this scheme is to make the compromise required between the route overhead and its optimality based on a user-defined utility function. We analytically derive the optimal discovery radius (k) that achieves this target. Evaluations on NS2 show that our scheme can enhance the current routing protocols in terms of throughput with minimal overhead.

In this paper, we study the problem of cooperative spectrum sharing among a primary user (PU) and multiple secondary users (SUs) under quality of service (QoS) constraints. The SUs network is controlled by the PU through a relay which gets a revenue for amplifying and forwarding the SUs' signals to their respective destinations. The relay charges each SU a different price depending on its received signal-to-interference-and-noise ratio (SINR). The primary relay controls the SUs network and maximize any desired PU utility function. The PU utility function represents its QoS, which is affected by the SUs access, and its gained revenue to allow the access of the SUs. The problem of maximizing the primary utility is formulated as a Stackelberg game and solved through three different approaches, namely, the optimal, the heuristic and the suboptimal algorithms.

Successful spectrum sharing in a cognitive radio network depends on the correct and quick detection of primary activity. Cooperative spectrum sensing is therefore suggested to enhance the reliability of such detection. However, it renders another significant problem of increased detection delay and traffic burden. Moreover, efficient schemes for multi-sensor data fusion should be designed. In this paper, we employ sequential detection scheme together with ordered transmissions from cognitive detectors. We derive two sequential schemes, one that is capable of achieving the minimum probability of error, and another that trades-off performance with delay. For the latter we derive expressions for the likelihood functions of ordered observations and compute the thresholds via backward induction. Simulation results demonstrate the relative performance of the approaches proposed in the paper.

Efficient resource allocation is a critical component in multi-user QoS communications and high speed networks. In this paper, we devise a new mathematical model for the resource allocation problem that takes into account the users' demands in a PHY-MAC cross-layer approach. Incorporating the time axis in our model, the target is to maximize the number of bits transmitted in a given frame rather than maximizing the channel capacity or the average throughput. Our design is governed by constraints on users' demands (expressed in bits), energy expenditure, and frame duration. We model the allocation problem as an optimization problem whose solution allocates channels, time span, and power levels to each user. We also derive an upper bound on the performance of any resource allocation algorithm and use this bound to assess the performance of the solution obtained using our proposed model.

In this paper, a cross-layer adaptive resource allocation (XARA) algorithm for channel division based systems, such as OFDMA, is proposed. XARA design is based on a PHY-MAC cross-layer approach which yields better channel utilization compared to separate PHY or MAC designs. XARA uses a joint power and channel allocation algorithm to determine both the channel assignment and the transmission power for each user in order to maximize the overall system capacity. Through an iterative algorithm, XARA enhances the channel utilization by taking into account the demands of the users so as to assign the minimum number of time slots needed to fulfill the requirements of each user. The saved time slots are reported to the scheduling and admission control functions of the MAC layer in order to either allow more users to enter the network or to allow the current users to request more quality of service "QoS" sessions. The proposed algorithm can fit in different wireless systems such as WIMAX and LTE. The algorithm is also flexible enough to accommodate the dynamic nature of the spectrum in the case of cognitive radio networks and considers the power constraints associated with such networks.

Spectrum scarcity is the major challenge facing all parties working in the telecommunications industry. As recently shown, the main problem of spectrum unavailability is due to spectrum inefficient utilization rather than spectrum scarcity. Inspired by this argument, a paradigm shift in spectrum management is achieved by the aid of smart radios called cognitive radios that can opportunistically access the available spectrum. In this context, we address the problems of power control and channel assignment jointly. Namely, given a set of available channels which is determined dynamically, we devise a near-optimal yet simple algorithm with linear complexity targeting capacity maximization of a cognitive radio network while jointly optimizing power and channel allocation among users (cognitive radios) while respecting total power constraints per individual users. In an extended version, we also consider a conservative design where signal-to-interference-plus-noise ratio (SINR) constraints at the primary users have are imposed. Simulated experiments illustrate the near optimal performance of the devised algorithm compared to the exhaustive search approach. Moreover, the limits of the system capacity are quantified given both ideal (no SINR constraints) and conservative (with SINR constraints) designs.

Emerging applications involving low-cost wireless sensor networks motivate well optimization of multi-user orthogonal frequency-division multiple access (OFDMA) in the power-limited regime. In this context, the present paper relies on limited-rate feedback (LRF) sent from the access point to terminals to minimize the total average transmit-power under individual average rate and error probability constraints. Along with the characterization of optimal bit, power and subcarrier allocation policies based on LRF, suboptimal yet simple schemes are developed for channel quantization. The novel algorithms proceed in two phases: (i) an off-line phase to construct the channel quantizer as well as the rate and power codebooks with moderate complexity; and (ii) an on-line phase to obtain, based on quantized channel state information, the optimum, rate, power and user-subcarrier allocation with linear complexity. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with suboptimal schemes based on practically affordable LRF.

Emerging applications involving low-cost wireless sensor networks motivate well optimization of multi-user orthogonal frequency-division multiple access (OFDMA) in the power-limited regime. In this context, the present paper relies on limited- rate feedback (LRF) sent from the access point to terminals to acquire quantized channel state information (CSI) in order to minimize the total average transmit-power under individual average rate and error probability constraints. Specifically, we introduce two suboptimal reduced-complexity schemes to: (i) allocate power, rate and subcarriers across users; and (ii) design accordingly the channel quantizer. The latter relies on the solution of (i) to design equally probable quantization regions per subcarrier and user. Numerical examples corroborate the analytical claims and reveal that the power savings achieved by our reduced-complexity LRF designs are close to those achieved by the optimal solution.

Emerging applications involving low-cost wireless sensor networks motivate well optimization of multi-user orthogonal frequency-division multiple access (OFDMA) in the power-limited regime. In this context, the present paper relies on limited-rate feedback (LRF) sent from the access point to terminals to minimize the total average transmit-power under individual average rate and error probability constraints. The characterization of optimal bit, power and subcarrier allocation policies based on LRF, as well as optimal channel quantization are provided. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with few fed back bits.

This letter addresses the problem of energy detection of an unknown signal over a multipath channel. It starts with the no-diversity case, and presents some alternative closed-form expressions for the probability of detection to those recently reported in the literature. Detection capability is boosted by implementing both square-law combining and square-law selection diversity schemes

Motivated by the increasing demand for low-cost low-power wireless sensor networks and related applications, we develop suboptimal but simple bit and power loading algorithms that minimize transmit-power for orthogonal frequency division multiplexing (OFDM) under rate and error probability constraints. Bit and power loading adaptation are based on a quantized version of channel state information (D-CSI) conveyed from the receiver to the transmitter. Our design exploits the correlation among sub-carriers in order to reduce feedback overhead. Numerical examples support our claim that simple suboptimal schemes with a reduced number of feedback bits achieve near-optimal performance while providing significant power savings

This paper aims at maximizing the spectral efficiency of the recently proposed hybrid FSK/QAM scheme by the authors. The optimization problem incorporates the notion of discrete rate and respects prescribed constraints on average power, probability of error, and peak power. Further, we highlight the impact on performance if we use a discretized version of optimum continuous rate versus optimum discrete rate. Numerical examples reflect that the former approach is inferior to the latter when sole QAM is considered whereas both approaches are almost identical when dealing with hybrid FSK/QAM.

In response to the growing demand for low-cost low-power wireless sensor networks and related applications, we develop bit and power loading algorithms that minimize transmit-power for orthogonal frequency division multiplexing (OFDM) under rate and error probability constraints. Our novel algorithms exploit one of three types of channel state information at the transmitter (CSIT): deterministic (per channel realization) for slow fading links, statistical (channel mean) for fast fading links, and quantized (Q-) CSIT whereby a limited number of bits are fed back from the transmitter to the receiver. By adopting average transmit-power as a distortion metric, a channel quantizer is also designed to obtain a suitable form of Q-CSI. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with a few bits of Q-CSIT.

Emerging applications involving low-cost wireless sensor networks motivate well optimization of orthogonal frequency-division multiplexing (OFDM) in the power-limited regime. To this end, the present paper develops loading algorithms to minimize transmit-power under rate and error probability constraints, using three types of channel state information at the transmitter (CSIT): deterministic (per channel realization) for slow fading links, statistical (channel mean) for fast fading links, and quantized (Q), whereby a limited number of bits are fed back from the transmitter to the receiver. Along with optimal bit and power loading schemes, quantizer designs and reduced complexity alternatives with low feedback overhead are developed to obtain a suite of Q-CSIT-based OFDM transceivers with desirable complexity versus power-consumption tradeoffs. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with a few bits of Q-CSIT

In response to the ongoing demand for low power applications, the two first authors have recently proposed in F.F. Digham and M.-S. Alouini (2004) a discrete-modulation and fixed-power non-coherent M-ary frequency shift keying scheme. In this paper, we propose an extension of that work by studying a discrete-modulation and continuous-power (DMCP) scheme for further power saving over Nakagami fading channels. The modulation level and power assignment are selected in order to minimize the average transmitted power while meeting average spectral efficiency and bit error rate constraints. We further investigate the problem with an additional peak power constraint. In this case, the modulation switching thresholds are shifted to higher values yielding reduction in both the achievable average spectral efficiency and the average transmitted power. However, the power loading function can be re-shaped to maintain the same average power of transmission for the cases on no-peak and with-peak power constraints. This reshaping is designed so as to involve constant power portions which can be of interest from a practical stand point

This paper revisits a selective diversity system with optimum continuous power loading which was originally proposed in Skinner and Cavers (February 1973) and which yields minimum average probability of error when the diversity paths are orthogonal. In a first part, the paper offers an alternative look at the system considered in T. A. Skinner and J. K. Cavers (February 1973) and provides some slightly modified results. In a second part, the paper considers a practical implementation of this system by proposing an optimum discrete power loading scheme. The problem in its discrete fashion is to minimize the average bit error rate for a given total energy constraint resulting in an optimum discrete power loading as a function of the channel status. This discrete implementation of the scheme makes the system more robust against imperfect and/or outdated channel estimates. In addition in this case only the index of the adaptation region (rather than the instantaneous channel status) has to he sent back to the transmitter.

This paper studies a system with diversity reception combining and adaptive discrete power of transmission based on an idea presented by J. F. Haves (February 1968) wherein he showed that feedback information improves the performance significantly in a Rayleigh multipath medium. We first have an alternative look at the system considered by J. F. Haves (February 1968) by providing slightly modified and compact results. We then consider the practical implementation of this system by proposing an optimum discrete power loading scheme. The problem in its discrete fashion is to minimize the average bit error rate for a given total energy constraint resulting in an optimum discrete power loading as a function of channel status. This discrete scheme also makes the system more robust against imperfect and/or outdated channel estimates and does not need to feedback the instantaneous channel status but instead the index of the adaptation region.

We propose a variable-rate and fixed-power noncoherent M-ary frequency shift keying (NC-MFSK) modulation scheme for power limited systems over Nakagami-fading channels. We first address the system performance from the average link spectral efficiency, the average bit-error rate (BER), and the probability of outage perspectives assuming that perfect channel estimates are available at the transmitter within a permissible delay. We compare the proposed system with two versions of the noncoherent binary FSK (NC-BFSK) scheme. The former is the fixed or the blind one, which has no feedback information, and the latter is a kind of an adaptive one wherein a feedback channel is provided to inform the transmitter whether to transmit or not. Our results show that the proposed adaptive MFSK scheme exhibits the following gains: up to a 9- and 37-dB power gain from the average spectral efficiency perspective compared to those for the adaptive and fixed NC-BFSK schemes, respectively, at very low values of the received carrier-to-noise ratio and improvements of about four orders and one order of magnitude from the average BER and probability of outage perspectives, respectively, compared to those of the fixed NC-BFSK scheme. We then study the system performance in the case of outdated estimates. It is shown that only the average BER gets affected by outdated estimates. Our analysis shows that the system is insensitive to normalized delays f/sub d//spl tau/ up to 10/sup -2/ where f/sub d/ is the doppler frequency and /spl tau/ is the time delay. We also propose an adaptive switching thresholds scheme to better mitigate the effect of the feedback delay.

Abstract Closed form expressions for the average probability of packet error (PPE) are presented for no diversity, maximum ratio combining (MRC), selection combining (SC) and switch and stay combining (SSC) diversity schemes. The average PPE for the no diversity case is obtained in two alternative expressions assuming arbitrarily correlated Nakagami and Rician fading channels. For the MRC case,Ldiversity branches are considered and the channel samples are assumed to follow Nakagami distribution and to be arbitrarily correlated in both time and space. For the SC diversity scheme withLdiversity branches, two bounds on the average PPE are derived for both slow and fast fading channels. The average PPE in this case is obtained in an infinite integral form for Nakagami channels while it is reduced to a closed form expression for the Rayleigh case. The average PPE is also derived in the case of SSC diversity with dual branches for both slow and fast Rayleigh fading channels. The new formulas are applicable for all modulation schemes where the conditional probability of error has an exponential dependence on the signal‐to‐noise ratio. The average PPE is then used to obtain a modified expression for the throughput for network protocols. In general, the diversity gain exhibits a little diminishing effect as the number of diversity branches increases. In addition, the system is found to be more sensitive to the space correlation than to the time correlation. The effects of different system parameters and diversity schemes are studied and discussed. Specific figures about the system performance are also provided. Copyright © 2004 John Wiley & Sons, Ltd.

This paper first addresses the problem of known signal detection over both Rayleigh and Nakagami fading channels. More specifically, it studies the effect of different diversity schemes as a remedy to improve the probability of detection. Maximum ratio combining, selection combining, and switch and stay diversity schemes over Rayleigh fading channels are investigated. Closed form expressions for the average probability of detection for no diversity and diversity cases are obtained. The second part of this paper deals with both generalized likelihood ratio and uniformly most powerful tests for unknown-signal detection over Rayleigh fading channels. For this purpose, a simple decision criterion assuming only the knowledge of the noise power spectral density and the signal bandwidth is provided.

The first two authors have proposed a variable-rate and fixed-power (VRFP) non-coherent M-ary frequency shift keying (M-FSK) scheme for power limited systems [F.F. Digham and M.S. Alouini (September 2002)], [F.F. Digham and M.S. Alouini (November 2002]. In this paper, we propose a variable-rate and variable-power (VRVP) scheme which offers some additional power saving. In this scheme, we impose the power assignment function as a design variable to minimize the objective function which is the average transmitted power while meeting the average spectral efficiency and bit error rate (BER) constraints. The power allocation mechanism is executed based on the channel gain feedback estimates. Our results show that the proposed system provides power saving varying from roughly 2.3 up to 5 dB. Moreover, the power loading function exhibits two interesting features. The first is that its peak is always less than the fixed amount of power used to guarantee the same system performance. The second is the self control type of behavior in which the peak occurs at a moderate value of channel gain while it tends to allocate less power at both high and low values of channel gain. We further investigate the problem with an additional maximum power constraint. In this case, we obtain a modified power loading function which can still fulfil the rate constraint up to a certain limit after which there is a rate maximum-power tradeoff.

This paper presents another look at the problem of energy detection of unknown signals over different fading channels. We start with the no diversity case and present some alternative closed-form expressions for the probability of detection (P/sub d/) to those recently reported in [V.I. Kostylev, May 2002]. We then investigate the system performance when different diversity schemes are employed. It is shown that there is not much improvement in the probability of detection when either the probability of false alarm (P/sub f/) exceeds 0/1 or the average signal-to-noise ratio (SNR) exceeds 20 dB. In addition, receiver operating characteristic (ROC) curves comparing the performance of equal-gain combining (EGC), selection combining (SC), and switch and stay combining (SSC) are presented. As an example, EGC introduces a gain of two orders of magnitude from the probability of miss perspective compared to the no diversity case while both SC and SSC introduce a gain of about one order of magnitude.

We propose a new adaptive scheme for power limited systems. For such systems, we offer a variable-rate and fixed-power non-coherent M-ary frequency shift keying (NC-MFSK) modulation scheme and analyze its performance over Nakagami fading channels. We recently addressed the system performance from the average link spectral efficiency, the average bit error rate (BER), and the probability of outage perspectives assuming that perfect channel estimates are available at the transmitter within a permissible delay. In this paper, we study the system performance in the case of outdated estimates. It is shown that only the average BER gets affected by outdated estimates. Our analysis shows that the system is insensitive to normalized delays f/sub d//spl tau/ up to 10/sup -2/ where f/sub d/ is the Doppler frequency and /spl tau/ is the time delay. We then propose an adaptive switching thresholds system to better mitigate the effect of the delay.

A closed form expression for the average probability of packet error (PPE) is presented for a maximum ratio combining (MRC) diversity scheme. The resulting expression encompasses arbitrarily correlated Nakagami and Rician fading channels. As an example, we focus on Nakagami fading channels of arbitrary correlation in both time and space. The new formulas are applicable for all modulation schemes for which the conditional probability of error has an exponential dependence on the signal-to-noise ratio (SNR). The average PPE is then used to obtain a modified expression for the throughput of any network protocol. The system in general exhibits approximately a uniform gain as the number of diversity branches increases. The system is found to be more sensitive to the space correlation than to the time correlation. The effects of different system parameters and correlation models are studied and discussed. Specific figures about the system performance are provided.

New expressions for the average probability of packet error in case of intermediate Nakagami (1960) fading channels are derived. The correlation among bits within the packet is assumed to obey the first order Markovian process. Both non-coherent frequency shift keying (NCFSK) and quadrature phase shift keying (QPSK) modulation schemes are addressed. The average probability of packet error is used to obtain an expression for the modified throughput for the non-persistent carrier sense multiple access (NPCSMA) protocol. The different fading parameters affecting the modified throughput expression such as the average signal to noise ratio (SNR), fading margin and correlation factor among bits of the same packet are also analyzed.