In this paper, we propose an adaptive opportunistic spatial modulation scheme (AOSM), in which, our unique opportunistic group-antenna-selection scheme is amalgamated with a simple phase alignment (PA) transmit pre-scaling to boost the transmit-diversity of SM. To characterize and analytically evaluate the AOSM, a comprehensive error performance analysis is presented with single antenna reception. We theoretically derive a tight upper-bound for the symbol error probability (SEP) in closed-form based on an improved union-bound. The exact explicit asymptotic formula of the SEP at high SNR is provided as well. These results demonstrate that the transmit-diversity of proposed AOSM-(multiple-input single-output) MISO scheme is not only successfully achieved, but also elevated to be equal to the number of antennas in each antenna group. Moreover, it also reveals an important performance trend: at high SNR, with a fixed number of transmit antennas and a given data-rate, the SEP performance of the AOSM-MISO scheme can be successively enhanced by utilizing less antennas groups and bigger size of the signal constellation, because of the increase in transmit-diversity. Furthermore, the PA-aided SM-MISO is a special case of our AOSM-MISO. We are the first to provide the exact transmit-diversity gain for this conventional system and show that the PA pre-scaling scheme only can not improve the transmit-diversity of SM. This result sharpens the empirical diversity approximation results proposed in the existing literature. Simulation results well validate the analytical derivations, and indicate that our AOSM system can effectively improve system performance with high transmit-diversity at low-complexity.

This paper investigates the relay selection (RS) problem for multi-hop full-duplex relay networks where multiple source-destination (SD) pairs compete for the same pool of relays, under the attack of multiple eavesdroppers. To enhance the physical-layer security, within a given coherence time, our objective is to jointly assign the available relays at each hop to different SD pairs to maximize the minimum secrecy rate among all pairs. Two RS schemes, optimal RS and suboptimal RS (SRS), are proposed for two-hop networks based on global channel state information (CSI) and only SD pairs CSI, respectively. Since all users can communicate within the same coherence time, our joint RS schemes are important for the user-fairness and ultra-reliable low-latency communications. To evaluate the performance, the exact secrecy outage probability of the SRS scheme is derived under two residual self-interference models. The asymptotic analysis shows that the SRS scheme achieves full diversity. A relay-based jamming scheme is also proposed by using unassigned relays for user communications. Finally, the two-hop RS schemes and the analysis are extended to the general multi-hop network with multiple eavesdroppers. The numerical results reveal interesting fundamental trends where the proposed schemes can significantly enhance the secrecy performance.

This paper studies the relay selection (RS) problem for full-duplex (FD) relay networks with multiple source-destination (SD) pairs under the attack of colluding eavesdroppers. Based on available channel state information (CSI), both optimal relay selection (ORS) and suboptimal relay selection (SRS) schemes are considered to maximize the minimum secrecy rate among all pairs in order to enhance the physical-layer security. The secrecy performance of the more practical SRS scheme is then evaluated in terms of intercept probability and diversity order. The SRS achieves full diversity when the gains of the main-to- eavesdropper and the main-to-interference channels increase asymptotically.

A novel opportunistic antenna selection aided spatial modulation, called opportunistic spatial modulation (OSM), is proposed, which exhibits an attractive system reliability enhancement with low complexity. Its unique features enable a comprehensive analytical framework, which is challenging to acquire with existing transmit-antenna-selection-aided spatial modulation (TASS-SM) schemes. Closed-form expression of improved union bound for the average symbol error probability (ASEP) of proposed OSM-MISO system is derived. Furthermore, we compare the proposed OSM with a prevalent existing TASS-SM scheme to confirm the feasibility and effectiveness of our scheme. Simulation results are provided to corroborate the analytical results.

We consider a distributed detection system for a wireless sensor network over slow-fading channels. Each sensor only has knowledge of quantized channel state information (CSI) which is received from the fusion center via a limited feedback channel. We then consider transmit power allocation at each sensor in order to maximize a J-divergence based detection metric subject to a total and individual transmit power constraints. Our aim is to jointly design the quantization regions of all sensors CSI and the corresponding power allocations. A locally optimum solution is obtained by applying the generalized Lloyd algorithm (GLA). To overcome the high computational complexity of the GLA, we then propose a low-complexity near-optimal scheme which performs very close to its GLA based counterpart. This enables us to explicitly formulate the problem and to find the unique solution despite the non-convexity of the optimization problem. An asymptotic analysis is also provided when the number of feedback bits becomes large. Numerical results illustrate that only a small amount of feedback is needed to achieve a detection performance close to the full CSI case.

This paper proposes an opportunistic spatial modulation (OSM) scheme where the transmit antennas are divided into K ≥ 1 equal groups, and the best antenna from each group is selected to form a K transmit antenna subset for implementing spatial modulation (SM). Thus, the activation of one antenna from the subset to transmit one of the M-ary modulation symbols achieves a data rate of log2(K) + log2(M) bits per channel use. Notably, special cases of OSM include conventional SM and pure single transmit antenna selection. To characterize and comparatively evaluate OSM, we first consider phase-shift keying modulation and derive a closed-form, improved union-bound of symbol error probability (SEP) with a single-antenna receiver. Explicit expressions for the SEP in the high signal-to-noise ratio regime are also presented. Extensions to quadrature amplitude modulation analysis and simulations of multiple-antenna reception case are also provided. Simulation results corroborate the analytical results and reveal the interesting interplay between the signal and spatial constellation diagrams. For a given number of transmit antennas and targeted data rate, asymptotically, the SEP can be minimized by using only one antenna group and the largest size of signal constellation, as this configuration achieves the full-diversity order.

We consider physical-layer security in a novel MISO cooperative overlay cognitive radio network (CRN) with a single eavesdropper. We aim to design an artificial noise (AN) aided secondary transmit strategy to maximize the joint achievable secrecy rate of both primary and secondary links, subject to a global secondary transmit power constraint and guaranteeing any transmission of secondary should at least not degrade the receive quality of primary network, under the assumption that global CSI is available. The resulting optimization problem is challenging to solve due to its non-convexity in general. A computationally efficient approximation methodology is proposed based on the semidefinite relaxation (SDR) technique and followed by a two-step alternating optimization algorithm for obtaining a local optimum for the corresponding SDR problem. This optimization algorithm consists of a one-dimensional line search and a non-convex optimization problem, which, however, through a novel reformulation, can be approximated as a convex semidefinite program (SDP). Analysis on the extension to multiple eavesdroppers scenario is also provided. Simulation results show that the proposed AN-aided joint secrecy rate maximization design (JSRMD) can significantly boost the secrecy performance over JSRMD without AN.

This paper considers the ergodic weighted sum rate maximization (WSRMax) problem for an underlay cognitive radio multiple input single output (MISO) broadcast channel. In this setting, a secondary network, consisting of a base-station with M transmit antennas and K single-antenna secondary users (SUs), is allowed to share the same spectrum with a primary user (PU), under an average total transmit power (ATTP) constraint and an average interference power (AIP) constraint at the PU receiver. We show that the ATTP constraint always remains active, and as the maximum ATTP Pav→ ∞, the ergodic WSR approaches infinity similar to conventional non-CR networks. We propose a novel low-complexity suboptimal beamforming scheme termed "Partially-Projected & Regularized Zero-Forcing Beamforming" (PP-RZFBF) with a close-form beamformer, by combining the regularized zero-forcing (RZF) with the channel projection idea, to achieve a tradeoff between maximizing secondary throughput and suppressing secondary multiuser interference as well as the interference on PU. In order to analyze and optimize the performance of this scheme, we employ the large system analysis technique, in the limit as M and K approach infinity with a fixed ratio r=K\M. This allows us to derive deterministic limiting approximations for the PP-RZFBF problem which enables us to determine asymptotically optimal beamformers for PP-RZFBF. In the large system limit, for the PP-RZFBF scheme, we also find that as Pav→ ∞, the interference on PU caused by the secondary transmission is asymptotically removed. A special suboptimal beamforming scheme called "CZFBF" is also considered, which involves zero forcing all the interference, including the secondary multiuser interference as well as the interference imposed on PU. Various interesting comparisons between PP-RZFBF and CZFBF are provided. Numerical simulations illustrate that the asymptotically optimal beamformers for the PP-RZFBF scheme provide an excellent performance even for finite-sized systems.

This paper considers the ergodic weighted sum rate (WSR) maximization problem for an underlay cognitive radio MISO broadcast channel, where a secondary network, consisting of a base-station with M transmit antennas and K single-antenna secondary users (SUs), is allowed to share the same spectrum with a primary user (PU), under an average transmit sum power (ATTP) constraint Pavand an average interference power (AIP) constraint on the PU. We show that the ATTP constraint is always active, and as Pav→ ∞, the ergodic WSR approaches infinity similar to the conventional non-CR network case. A low-complexity suboptimal beamforming scheme (called partially-projected regularized zero-forcing beamforming `PP-RZFBF') with a closed-form beamformer is proposed. Due to the non-convexity of PP-RZFBF scheme, a large system analysis is conducted in the limit as M and K approach infinity with a fixed finite ratio r = K/M. We derive deterministic limiting approximations for the PP-RZFBF problem which enables us to determine asymptotically optimal beamformers for PP-RZFBF. Numerical simulations illustrate that the asymptotically optimal beamformers turn out to be quite effective even for small M, K.

We address an optimal transmit power allocation problem that minimizes the outage probability of a secondary user (SU) who is allowed to coexist with a primary user (PU) in a narrowband spectrum sharing cognitive radio network, under a long term average transmit power constraint at the secondary transmitter (SU-TX) and an average interference power constraint at the primary receiver (PU-RX), with quantized channel state information (CSI) (including both the channels from SU-TX to SU-RX, denoted as g1and the channel from SU-TX to PU-RX, denoted as g0) at the SU-TX. The optimal quantization regions in the vector channel space is shown to have a "stepwise" structure. With this structure, the above outage minimization problem can be explicitly formulated and solved by employing the Karush-Kuhn-Tucker (KKT) necessary optimality conditions to obtain a locally optimal quantized power codebook. A low-complexity near-optimal quantized power allocation algorithm is derived for the case of large number of feedback bits. More interestingly, we show that as the number of partition regions approaches infinity, the length of interval between any two adjacent quantization thresholds on the g0axis is asymptotically equal when the average interference power constraint is active. Similarly, we show that when the average interference power constraint is inactive, the ratio between any two adjacent quantization thresholds on the g1axis becomes asymptotically identical. Using these results, an explicit expression for the asymptotic SU outage probability at high rate quantization (as the number of feedback bits goes to infinity) is also provided, and is shown to approximate the optimal outage behavior extremely well for large number of bits of feedback via numerical simulations. Analysis on the extension to multiple secondary users case (cognitive multiple-access network) is also discussed. Numerical results illustrate that with only a few bits of feedback, the derived algorithms provide secondary outage performance very close to that with full CSI at the SU-TX.

A shot-noise limited single-user single-input single-output (SISO) Poisson fading channel with partial channel state information (CSI) at the transmitter and perfect CSI at the receiver is considered. We address an optimal transmit power allocation problem that maximizes the ergodic capacity of the SISO Poisson fading channel subject to peak and average power constraints with only quantized CSI available at the transmitter, acquired via a no-delay and error-free feedback link with finite-rate from the receiver to the transmitter. Due to the non-convexity of the proposed optimization problem, a globally optimum solution is difficult to obtain. However, we manage to obtain a locally optimal quantized power allocation (QPA) scheme by solving its dual Lagrangian optimization problem. We develop two efficient optimal QPA algorithms for solving the dual optimization problem and show that both of these algorithms converge to the globally optimal solution of the dual problem. A low-complexity near-optimal QPA algorithm is also derived for the case of large number of feedback bits. The results are then extended to the high peak signal-to-noise ratio (SNR) regime and an explicit expression for the approximate asymptotic ergodic capacity behavior in the high SNR regime with high rate quantization (as the number of feedback bits goes to infinity) is also provided. It is seen via numerical simulations that this asymptotic capacity expression correctly approaches the capacity of the corresponding full CSI case as the number of feedback bits becomes large. Finally, the effectiveness of the derived algorithms is examined through numerical simulations.

We consider a wideband spectrum sharing system where a secondary user can access a number of orthogonal frequency bands each licensed to a distinct primary user. We address the problem of optimum secondary transmit power allocation for its ergodic capacity maximization subject to an average sum (across the bands) transmit power constraint and individual average interference constraints on the primary users. The major contribution of our work lies in considering quantized channel state information (CSI) (for the vector channel space consisting of all secondary-to-secondary and secondary-to-primary channels) at the secondary transmitter as opposed to the prevalent assumption of full CSI in most existing work. It is assumed that a central entity called a cognitive radio network manager has access to the full CSI information from the secondary and primary receivers and designs (offline) an optimal power codebook based on the statistical information (channel distributions) of the channels and feeds back the index of the codebook to the secondary transmitter for every channel realization in real-time, via a delay-free noiseless limited feedback channel. A modified Generalized Lloyds-type algorithm (GLA) is designed for deriving the optimal power codebook, which is proved to be globally convergent and empirically consistent. An approximate quantized power allocation (AQPA) algorithm is presented, that performs very close to its GLA based counterpart for large number of feedback bits and is significantly faster. We also present an extension of the modified GLA based quantized power codebook design algorithm for the case when the feedback channel is noisy. Numerical studies illustrate that with only 3-4 bits of feedback per band, the modified GLA based algorithms provide secondary ergodic capacity very close to that achieved by full CSI and with only as little as 4 bits of feedback per band, AQPA provides a comparable performance, thus making it an attractive choice for practical implementation.