In this paper, we investigate the achievable rate and the average sum capacity of an underlay cognitive radio (CR) (also known as a secondary) system. We consider single user (SU) and multiple users (MU) secondary systems that deploy spread spectrum as the signaling technique which utilizes the whole available spectrum. The objective is to maximize the achievable rate and the average sum capacity of the SU and MU secondary systems, respectively, by allocating the optimum power to the secondary transmitter(s) (STs), such that the instantaneous (aggregate) interference power from STs is below a certain threshold at the primary receiver (PR), to guarantee the quality of service (QoS) of the primary system. Numerical and Monte-Carlo Simulation results show that the achievable rate of the SU system and the average sum capacity of the MU system can be enhanced significantly compared to other signaling techniques, because of the fact that in spread spectrum the signal's power is spread over a wider bandwidth, which gives the secondary system more freedom to allocate power to enhance the data rate.

Convolutional doubly orthogonal (CDO) codes constitute a recent group of binary error correcting codes for additive white gaussian noise channel, achieving very good error performance at moderate values of E b / N 0 under the threshold decoding algorithm. Inspired by the low‐density parity‐check codes over the finite fields, this study extends the construction and decoding of single shift register CDO codes from binary field to the finite fields GF ( q ) for q > 2, referred to as the q ‐ary CDO codes. The threshold decoding algorithm is modified to accommodate the decoding requirement for this set of codes. Superior error performance has been observed for q ‐ary CDO codes over their binary counterparts, especially in the error floor region.

In this paper we consider an Interference Alignment (IA) approach for intercell interference coordination for the downlink of a MIMO multi-user cellular network. We determine the maximum degrees of freedom (DoF) of the network and give the feasibility proof of perfect IA. Furthermore, we consider the problem of approximate IA and the Mean-Squared Error (MSE) based optimization of the transmit and receive beamforming matrices with the orthogonality constraints and the per-antenna transmit power constraint. Iterative algorithms are presented to solve the corresponding MSE problems. Simulation results and convergence analysis of the algorithms are also discussed. The results indicate that it is feasible to significantly increase the network capacity using the proposed IA approach.

In this paper we present an attractive alternative to construct time-invariant Low-Density Parity-Check Convolutional Codes (LDPC-CC) of coding rate-b/c from a simple recursive systematic convolutional encoder design. The proposed Recursive Convolutional Doubly-Orthogonal (RCDO) encoders have a corresponding Tanner graph for which the girth is controlled by the doubly-orthogonal conditions that are imposed onto the set of generators that represent the encoder. Therefore, RCDO encoders can be decoded using simply a cascade of the same threshold decoder. The convergence behavior of the iterative decoder is then controlled by the position and by the number of forward and feedback connections that constitute the encoder. RCDO encoders give rise to a class of capacity approaching codes that use simple encoder and decoder structures.

This letter presents a novel approach for deriving a lower bound on the outage probability of interference cancellation receiver in ad hoc networks for a class of channel fading. Our approach is based on the following observation: under the power decay law model for large-scale fading with an exponent ¿ strictly greater than 2, the sum of the interferences at a receiver has the same order as the strongest signal. This feature still holds when the small-scale fading has a finite 2/¿-fractional moment. This fact is used to develop an approximation which is also a compact lower bound on the outage probability.

This paper studies the performance of antenna array processing in distributed multiple access networks without power control. The positions of nodes are determined by a Poisson point process. Desired and interfering signals are subject to both path-loss (with an exponent greater than 2) and to independent Rayleigh fading. Using these assumptions, we derive the exact closed form expression for the cumulative distribution function of the output signal-to-interference-plus-noise ratio when optimum combining is applied. This results in a pertinent measure of the network performance in terms of the outage probability, which in turn provides insights into the network capacity gain that could be achieved with antenna array processing. We present and discuss examples of applications, as well as some numerical results.

In this paper, coded modulation technique based on the use of convolutional self-doubly orthogonal codes (CSO2C) and threshold iterative decoding is presented. Two different methods of coded modulation are considered. The first approach is based on a conventional pragmatic scheme. In the second approach, all information bits are coded and a simpler Gray coding is used for the bit-to-symbol mapping. Simulation results indicate that for a bit error rate of 10-5, the pragmatic 8-PSK coded modulation scheme with R = 2/3 coding rate provides a coding gain of 3 dB as compared with the error performances of the uncoded QPSK system. The simulation results also demonstrate that by using the second approach, a larger coding gain of 4.5 dB is obtained when compared with uncoded QPSK modulation.

A class of orthogonal convolutional codes featuring self-doubly-orthogonal properties is analyzed under iterative decoding techniques. The self-doubly-orthogonal properties of these codes allow them to approach the asymptotic error performance using a low complexity iterative threshold decoding algorithm. It can be shown that convolutional self-doubly-orthogonal codes are also suited for iterative belief propagation (BP) decoding algorithm with typically five iterations to approach the asymptotic error performance. At a substantially reduced complexity, iterative threshold decoding requires the same number of iterations as iterative BP decoding to achieve practically the asymptotic error performance at moderate signal-to-noise ratios.

A new class of convolutional self-doubly orthogonal codes which can be decoded by an iterative threshold decoder is presented. This new type of codes, called simplified convolutional self-doubly orthogonal codes (S-CSO2C), are obtained by simplifying some of the conditions on the double orthogonality of the convolutional self-doubly orthogonal codes (CSO2C). The relaxing of these conditions yields a substantial reduction of the total decoding delay induced by the memory length of the convolutional encoder at a cost of any a small degradation of the error performances. These simplified codes are also amenable to high coding rates R = b/(b + 1), b > 1 by puncturing a rate 1/2 systematic convolutional encoder. These new simplified CSO2C provide an interesting alternative for low complexity implementation error correcting schemes.

An algebraic construction for a class of low-density parity-check (LDPC) convolutional codes is presented on the basis of difference families associated with the code generator matrix. It can be shown that these codes have girth of at least 10 on the Tanner graph which is independent of either the size of the code generator matrix or the minimum Hamming distance of the codes. The code construction guarantees the independence of the messages exchanged in the belief propagation decoding process during two successive decoding iterations. Computer simulations show that over the additive white Gaussian noise channel, the best error performance of these codes at moderate signal-to- noise ratio values is practically obtained using only three to five iterations.

In this paper we present an analysis of the outage probability in DS-CDMA ad hoc network using interference cancellation receiver under a path loss attenuation channel model. A simple conceptual tool that gives a closed form approximation of the outage probability with variable precision on the interference cancellation is developed.

The complexities of iterative belief propagation decoding techniques for randomly constructed low-density parity-check (LDPC) block codes and nonrecursive convolutional self-doubly-orthogonal codes (CSO2Cs) are analyzed and compared on the basis of their decoding latencies expressed in the number of code symbols. Although, in principle, they have the same computational complexities, the pipeline decoder structure for CSO2Cs has a much smaller implementation complexity than the block decoder structure for LDPC block codes, but at a cost of small loss in the error performance of decoding.

A novel approach for the algebraic construction of low-density parity-check (LDPC) convolutional codes is presented. It is based on the orthogonality structures of the codes. The proposed code construction leads to a girth of at least 10 in the Tanner graph. The error performance of these codes compares favorably with the usual LDPC convolutional codes, especially at low signal-to-noise ratio range.

The complexities and latencies of iterative belief propagation (BP) and threshold decoding techniques for a new class of convolutional self-orthogonal codes are analysed using forward-only pipeline architectures. Computer simulation results show that over the additive white Gaussian noise channel at moderate signal-to-noise ratios, BP decoding yields one half the decoding delay when compared with threshold decoding at essentially the same error performances. However, the reduction in the decoding delay using BP is obtained at the cost of an increase of the implementation complexity.

In this paper a new class of high-rate punctured convolutional codes that can be decoded using an iterative threshold algorithm is proposed. These codes are called simplified punctured convolutional self-doubly orthogonal codes (S-PCSO2C) of rate-R=b/(b+1), b>1 and are obtained by puncturing a rate 1/2 systematic convolutional mother code. S-PCSO2C are codes for which the original set of conditions, respected by PCSO2C, is simplified. Relaxing the doubly orthogonal conditions yields an important reduction of the constraint length of the systematic convolutional encoder which in turn reduce the implementation complexity and the total decoding latency at the cost of a very small performance degradation.

The forward-only iterative decoding techniques for convolutional self-doubly-orthogonal codes are systematically presented based on one-step belief propagation (BP) decoding and one-step threshold decoding. A feedback mechanism and a weighing technique are examined in order to improve both the convergence speed and error performance. Computer simulation results show that compared with the iterative threshold decoding over an additive white Gaussian noise channel, the iterative BP decoding for these codes achieves essentially the same error performance while requiring only about half the number of iterations. Therefore, these two iterative decoding techniques can provide a tradeoff between the latency and the complexity of decoding and allow for the applications of these codes in very high speed wireless communications.

A procedure for the forward-only iterative belief propagation decoding of orthogonal convolutional codes is presented. It can be dramatically simplified to perform the iterative threshold decoding of convolutional self-doubly-orthogonal codes without interleaving. These procedures can help implement iterative decoders efficiently using a serial concatenation of one-step BP decoders or one-step threshold decoders, respectively. Simulations have shown that the error performance of orthogonal convolutional codes can be improved by iterative decoding whether based on belief propagation decoding or threshold decoding. For convolutional self-doubly-orthogonal codes, iterative threshold decoding can achieve the same error performance as iterative belief propagation decoding, but with greatly reduced decoding complexity, allowing an advantageous tradeoff between implementation complexity and latency.

A variant of convolutional self doubly orthogonal codes that can be decoded using an iterative threshold decoding algorithm is presented. These new codes are called degenerate convolutional self-doubly orthogonal codes since not all the double orthogonality conditions required to obtained convolutional self doubly orthogonal codes defined in the wide sense are satisfied. The memory lengths or spans of the degenerate convolutional self-doubly orthogonal codes are substantially shorter than those of the usual convolutional self doubly orthogonal codes defined in the wide sense, at the cost of only a slight degradation of the error performances. As a consequence, very low complexity implementations are possible with these error correcting schemes. Several new degenerate convolutional self doubly orthogonal codes have been determined and their error performances evaluated using computer simulations.

An efficient parallel processing mode is proposed for the implementation of fast forward-only iterative belief propagation decoding of orthogonal convolutional codes based on one-step decoding. In the proposed parallel processing mode, the iterative decoding of orthogonal convolutional codes makes use of the complete set of orthogonal parity-check equations on each information symbol, thus avoiding the error performance loss. The proposed parallel processing allows the speed of iterative decoding to approach that of one-step decoding. Therefore, an advantageous tradeoff can be available between data rate and latency.

The puncturing technique allows obtaining high-rate convolutional codes from low-rate convolutional codes used as mother codes. This technique has been successfully applied to generate good high-rate convolutional codes which are suitable for Viterbi and sequential decoding. In this paper, we investigate the puncturing technique for convolutional self-doubly orthogonal codes (CSO/sup 2/C) which are decoded using an iterative threshold-decoding algorithm. Based on an analysis of iterative threshold decoding of the rate-R=b/(b+1) punctured systematic CSO/sup 2/C, the required properties of the rate-R=1/2 systematic convolutional codes (SCCs) used as mother codes are derived. From this analysis, it is shown that there is no need for the punctured mother codes to respect all the required conditions, in order to maintain the double orthogonality at the second iteration step of the iterative threshold-decoding algorithm. The results of the search for the appropriate rate-R=1/2 SCCs used as mother codes to yield a large number of punctured codes of rates 2/3/spl les/R/spl les/6/7 are presented, and some of their error performances evaluated.

In this paper, we present new results on the search and determination of wide-sense convolutional self-doubly orthogonal codes (CSO/sup 2/C-WS) which can be decoded using a simple iterative threshold decoding algorithm without interleaving. For their iterative decoding, in order to ensure the independence of observables over the first two iterations without the presence of interleavers, these CSO/sup 2/C must satisfy specific orthogonal properties of their generator connections. The error performances of CSO/sup 2/C, depend essentially on the number of taps J of the code generators but not on the code memory length. Since the overall latency of the iterative threshold decoding process is proportional to the memory length of the codes, therefore, when searching for the best CSO/sup 2/C-WS of a given J value, the memory length of the codes should be chosen to be as small as possible. In this paper, we present a code-searching technique based on heuristic computer searching algorithms which have yielded the best known CSO/sup 2/C-WS. The construction method for CSO/sup 2/C-WS has provided the best known r=1/2 codes with the shortest memory length having J/spl les/30. Although not very complex to implement, the search method presented here is quite efficient especially in reducing very substantially the execution time required to determine the codes with the shortest spans. Furthermore, in addition to presenting the search results for the codes, error performances obtained by simulation are also provided.

A class of forward-only iterative belief propagation algorithms for decoding convolutional self-orthogonal codes is presented, which perform successively a number of one-step decoding and thus have only an initial decoding delay. The one-step belief propagation decoders can be realized in a similar way to one-step threshold decoders. The error performance of the algorithms is easily improved by using a weighing technique. These iterative algorithms allow good tradeoffs between complexity, latency, and error performance of the coding scheme.

An extension of convolutional self-orthogonal codes called convolutional self-doubly orthogonal codes which are decoded using an iterative threshold decoding algorithm with no interleaver is presented. These new codes allow good error performance in addition to providing attractive trade-off between complexity and latency. Some code searching results yielding new codes are provided together with their error performance evaluation. Puncturing techniques for systematic convolutional codes that allows us to obtain high-rate R = b/(b + 1) punctured convolutional self-doubly orthogonal codes in the wide sense are also investigated. Some punctured convolutional self-doubly orthogonal codes are presented and their bit error probabilities are evaluated using computer simulations.

A novel iterative error control technique based on the threshold decoding algorithm and new convolutional self-doubly orthogonal codes is proposed. It differs from parallel concatenated turbo decoding as it uses a single convolutional encoder, a single decoder and hence no interleaver, neither at encoding nor at decoding. Decoding is performed iteratively using a single threshold decoder at each iteration, thereby providing good tradeoff between complexity, latency and error performance.

In this paper we present a novel iterative error control technique which circumvents both the complexity and latency shortcomings of the usual turbo codes. It differs from usual turbo coding techniques as it uses a single encoder (hence with no interleaver at the encoding process) and a single decoder. The technique is based on a novel class of orthogonal threshold decodable codes called convolutional self doubly orthogonal codes (CSO/sup 2/C).