Massive Multiple Input Multiple Output (m-MIMO) stands as a fundamental technique for the evolution of next-generation (5G Advanced and 6G) wireless communication networks. Although suboptimal, the classic zero-forcing (ZF) and Minimum Mean Square Error (MMSE) detectors suffer from high computational complexity in the calculation of matrix inverses. Since the computational complexity of all the signal detection techniques is directly proportional to the number of antennas at the base station, with the ever-increasing number of base station antennas in 6G, the other iterative detection methods don't resolve the critical issue of computational complexity. Consequently, there is a need for signal detection techniques with low computational complexity. This paper proposes a novel, highly efficient detection technique achieved through dimensionality reduction of the channel matrix and an approximate inverse of the Gram matrix. A groundbreaking outcome of this paper is the proposed detector's computational complexity being independent of the number of base station antennas, a feature especially valuable in extreme m-MIMO scenarios. Simulation results demonstrate performance comparable to the ZF detector, with computational complexity reduced to less than 5% of conventional detection methods.

As Cyclic Redundancy Check (CRC) codes offer the advantages of low power transmission and variable payload length, they have found applications in IoT standards like IEEE 802.15.4 and Bluetooth low energy (BLE). Despite having redundant bits, CRC codes are merely used as error-detecting codes due to the unavailability of a suitable decoder. Several efforts have been made to design a decoder for CRC to use as error-correcting code. The recently proposed GRAND algorithm serves as an error-correcting algorithm for CRC but has huge complexity. In this paper, a low complexity hard decision decoder is proposed for CRC with $g(x)=1+x^{5}+x^{12}+x^{16}$ which is used in IEEE 802.15.4 for IoT applications. The proposed decoder utilizes channel state information (CSI) for decoding in a Rayleigh fading channel and attained fourth-order diversity with very low complexity. The proposed decoder is especially effective at short block lengths; hence it serves as a sound decoder catering to IoT and URLLC services.

Application specific instrumentation (ASIN) makes use of sensors and AI (SensAI) algorithms for a highly specialized application, using less computational overhead, it can give good performance. This work evaluates the performance of communication based sensing (CommSense) system using Principal Component Analysis (PCA), kernel PCA (KPCA), t-distributed Stochastic Neighbour Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) algorithms and their quality of projection. In this paper, we have used Earth Mover’s Distance (EMD) (also known as 1stWasserstein Distance (WD)) for assessing the projections and we reach at the conclusion that, in terms of implementation PCA is the best, but for visualization KPCA, t-SNE and UMAP perform better than PCA.

User equipment (UE), in general, has access to multiple radio access technologies (RATS). Besides, secondary base-stations can also aid the UE's communication. Thus data can reach the UE from the primary base-station via multiple secondary base-stations. Taking advantage of the benefits of using such multiple paths, we propose in this paper a cross-layer scheme that improves block error rate (BLER) and throughput. We propose data duplication and integration at the Packet Data Convergence Protocol (PDCP) sublayer of layer 2 for downlink operations of 4G LTE / 5G NR. At the PDCP of ENodeB (gnodeB), the PDCP protocol data unit (PDU) is duplicated and sent to the UE via various paths. All these PDUs have the same sequence number (SN). Data from various networks are aptly linked using the PDCP assigned SN at EnodeB to obtain a composite and improved version of the PDU at UE. Although the cross-layer technique involves new procedures when combining data at PDPCP, the average delay for a PDCP-based aggregation scheme is very small compared with the standalone scheme because of the significant improvement in the block error rate (BLER) provided by the scheme over the BLER of the traditional standalone system. Finally, the BLER improvement results in throughput enhancement.

In this paper, we propose a channel reservation scheme for a cognitive radio network where a fraction of channels are strictly reserved for the Primary user (PU) transmissions only. The PU's and the SU's data packets arrive according to a Poisson process. We develop a probabilistic model for the PU occupancy and the probabilities of transmission with and without interference. Using this occupancy model we characterize the PU's and the SU's average achievable data rate when the PU faces spectrum sensing errors. We then show that using a reservation based scheme significantly improves the PU data rate at a marginal loss to the SUs data rate. We also derive the optimal number of channel to be reserved that maximizes sum rate.

This paper considers the cooperative spectrum sensing (CSS) in a cognitive radio (CR) network, where K secondary users (SUs) are used to determine the primary user's (PU's) signal using the m-out-of-K rule. In CR networks, the SUs must opportunistically utilizes to the PU's channel without affecting the quality of service of the PU. Therefore, we aim to optimize the m value and the K value of the m-out-of-K rule to achieve the maximum channel throughput of the CR network (throughput of the PU plus throughput of the secondary network) under sufficient protection to the PU. The results are illustrated using the energy detector.

This letter considers cooperative spectrum sensing (CSS) in a heterogeneous cognitive radio network, where K nonidentical cognitive users (CUs) and a fusion center (FC) collaboratively detect the primary user's signal using the N-out-of-K rule in the presence of erroneous control channels. We formulate a generalized optimal fusion problem (GOFP) to optimize the Nout-of-K rule for the Bayesian test and then solve the GOFP to obtain the optimal value of N. It follows that existing results on the optimal value of N in the N-out-of-K rule are special cases of the proposed solution. We then propose a framework to obtain the smallest number of CUs required in CSS while satisfying a target error bound at the FC. Numerical results are presented using the energy detector as an example.

The non-randomized optimal hard decision fusion under Neyman-Pearson criterion is known to be an NP-hard classical 0-1 Knapsack problem with exponential complexity. In this paper, we show analytically that though the low-complexity non-randomized single-threshold likelihood ratio based test (non-rand-st LRT) is sub-optimal, its performance approaches the upper-bound obtained by randomized LRT (rand LRT) with the increase in the number of participating sensors (N). This alleviates the need for employing the exponentially complex non-randomized optimal solution for large N. Receiver operating characteristics are plotted to verify the performance of the non-rand-st LRT with reference to the upper-bound obtained by rand LRT for different scenarios.

The Maximum Likelihood Detector (MLD) offers an optimal bit-error-ratio for an un-coded multiple-input-multiple-output (MIMO) communication system. The computational complexity, however, of MLD increases significantly for detection of higher order modulated signal streams with multiple transmit antennas. To reduce this complexity while simultaneously also achieving near optimal performance, we propose a novel technique that modifies the sub-optimal Zero Forcing Detector (ZFD) by using the minimum eigen vector of the matrix HHH, where H is the channel matrix and HHis its Hermitian. The performance in terms of BER and computational complexity of the proposed technique is compared to that of the MLD. Simulations show that the BER performance of the proposed technique is near optimal whereas the computational complexity is significantly reduced.

In this letter, we propose novel (semi)blind hard decision fusion rules that use the mean of the secondary user characteristics instead of their actual values. We show that these rules with slight (or no) additional system knowledge achieve better receiver operating characteristics than existing (semi)blind alternatives. These rules also have a low-complexity analytical solution under Neyman-Pearson criterion in some relevant cases. Numerical results are reported in a channel-aware scenario to demonstrate their appeal and to confirm the theoretical findings.

The design of the optimal nonrandomized hard decision fusion rule under the Neyman-Pearson criterion is known to be exponential in complexity. In this letter, we formulate a more generalized version of this problem called the “generalized decision fusion problem (GDFP)” and relate it to the classical 0-1 knapsack problem. Consequently, we show that the GDFP has a worst-case polynomial time solution. Numerical results are presented to verify the effectiveness of the proposed solution.

In this paper, a novel approach for solving the `Water- filling problem with peak power constraints for individual resources' also known as Cave-Filling Problem (CFP) is proposed. The proposed algorithm calculates a lower bound for the number of resources that are assigned positive powers, K, and then calculates the K powers only once. This lowers the total computational cost of the proposed algorithm significantly. Simulation results validate the proposed algorithm.

In this paper, we present expressions for optimal number of secondary users (SUs) by minimizing the global error rate for a given fusion rule at the fusion center (FC). Expressions for optimal number of SUs are presented for AND, OR and MAJORITY fusion rules. We show that optimal number of SUs depends on effective probability of false alarm (Pfe) and effective probability of miss detection (Pme) of a SU over erroneous control channel. Using improved energy detector as an example feasibility regions are derived for OR, AND and MAJORITY rules.

Waterfilling problems subjected to peak power constraints are solved, which are known as cave-filling problems (CFP). The proposed algorithm finds both the optimum number of positive powers and the number of resources that are assigned the peak power before finding the specific powers to be assigned. The proposed solution is non-iterative and results in a computational complexity, which is of the order of M, O(M), where M is the total number of resources, which is significantly lower than that of the existing algorithms given by an order of M2, O(M2), under the same memory requirement and sorted parameters. The algorithm is then generalized both to weighted CFP (WCFP) and WCFP requiring the minimum power. These extensions also result in a computational complexity of the order of M, O(M). Finally, simulation results corroborating the analysis are presented.

In this paper we optimize the n-out-of-K voting rule by minimizing the global error rate for cooperative spectrum sensing with single bit reporting over erroneous control channel, when all the K users are similar. We show that the optimal choice of n i.e. n* depends on the operating SNR, probability of error over control channel, Pe, and the threshold, v, used by the K users. We then derive the expressions of Receiver operating Characteristics (RoC) curves applicable to any detector where AND, OR and majority rule is optimal. Results are verified by using energy detector. Since the RoC expressions are complex, additional insight is obtained by deriving feasible region for OR and AND rule. It is observed that 1) OR and AND rule are never optimal, for practical cases, 2) In contrast to the case with error free control channels, Majority rule is not always optimal if the effective probability of false alarm and the probability of miss detection are of the same order.

In this paper, we propose a generalized model for underlay based cognitive radio (CR) that is based on the information theoretic interference channel model. Utilizing the achievable rate region for the two user interference channel proposed by Han and Kobayashi, we establish achievable rates for the unlicensed or the Secondary User (SU) that depends upon a given target rate for the licensed or the Primary User. Hence, the transmission of the SU is rate limited due to the PU achievable rate. Unlike the traditional approach for underlay, our results bring out the impact of SU transmission on the set of achievable rates for the PU and also of the effect of PU target rate (which may be called its QoS) on the set of achievable rate for the SU.

In this letter, we present a novel method of solving the Generalized Waterfilling problem (GWFP) using equivalence with a waterfilling problem (WFP) which has a closed form solution. Consequentially, a class of WFPs with only one-step called `1-step' WFP is used to derive a low complexity algorithm which has the smallest worst case complexity reported. The proposed algorithm is verified by simulations.

In this demo, we demonstrate integration of cognitive radio capabilities, on the fly, with GSM base station (BTS) using OpenBTS architecture. The demonstration has following novel features: Cognitive sensing of the channel, in use by secondary user, while transmitting, On the fly shifting to free GSM subchannel without call drop, Works with existing GSM phones without any modification in hardware and software. Trials at IIT Hyderabad over the last one year has validated the viability of the system.

In this paper we derive the optimal space-time power allocation scheme that minimizes the BER for MIMO fading channels when ideal channel state information (CSI) is available at the transmitter and receiver. We then show that this scheme achieves exponential diversity. Simulation results corroborating the theoretical analysis are then presented for MIMO Rician fading channels where we show that for two transmit and two receive antennas the presented scheme achieves more than 3 dB gain over best known Power Allocation Schemes.

In this paper we derive conditions under which exponential diversity can be achieved when the quality of channel state information degrades. We show that exponential diversity is obtained if and only if the variance of the noise corrupting the CSIT is (atleast) inversely proportional to SNR and the channel estimate is obtained at a transmit power greater than or equal to the power to be allocated. Simulation results, corroborating the theoretical analysis are presented for Rayleigh fading channels.

Fast Fourier Transform (FFT) is one of the most basic and essential operation performed in software defined radio (SDR). Therefore designing a universal, reconfigurable FFT computation block with low area, delay and power requirement is very important. Recently it is shown that Bruun's FFT is ideally suited for SDR even when operating with higher bit precision to maintain same NSR. In this paper, authors have proposed a new architecture for Bruun's FFT using a distributed approach for incrementing the number of bits (precision) with successive stages of FFT. It is also shown that proposed architecture further reduces the hardware requirement of Bruun's FFT with negligible changes in it's NSR. The proposed design makes Bruun's FFT, a better option for most practical cases in SDR. A detailed comparison of Bruun's traditional and proposed hardware architectures for same NSR is carried out and results of FPGA and ASIC implementations are provided and discussed.

A comb spectrum evaluation problem arises in the channel estimation of pilot symbol-assisted modulation (PSAM) systems and also in the (de) modulation of multichannel communication system based on orthogonal frequency division multiplexing (OFDM). In this paper we decompose a M-component comb spectrum evaluation with transform length N into i) a FFT evaluation of transform length M of a length M vector, ii) which in turn is obtained from the length N input vector (by folding and scaling). This decomposition allows for the application of split-radix and radix-4 algorithms for evaluation of M length transform and efficient computation of the length M vector from the length N input vector, which is classically termed as 'pruning'. When N = 2p, the comb spectrum computation requires only N/8+M/3log2M nontrivial complex multiplications, if N/M - 8. In addition, conditions under which comb spectrum evaluation can be done in O(M log M) complex multiplies are identified.

A comb spectrum evaluation problem arises in the channel estimation of pilot symbol-assisted modulation (PSAM) systems and also in the (de)modulation of multichannel communication system based on orthogonal frequency division multiplexing (OFDM). In this letter, we decompose an M-component comb spectrum evaluation with transform length N into 1) a fast Fourier transform evaluation of transform length M of a length M vector, 2) which in turn is obtained from the lengthN input vector (by folding and scaling). This decomposition allows for the application of split-radix and radix-4 algorithms for evaluation of M length transform and efficient computation of the length M vector from the length N input vector, which is classically termed as "pruning." When N=2p, the comb spectrum computation requires only N/8+M/3log2M nontrivial complex multiplications, if N/Mges8. In addition, conditions under which comb spectrum evaluation can be done in O(MlogM) complex multiplies are identified

Space-time block codes (STBCs) from orthogonal designs (ODs) and coordinate interleaved orthogonal designs (CIOD) have been attracting wider attention due to their amenability for fast (single-symbol) maximum-likelihood (ML) decoding, and full-rate with full-rank over quasi-static fading channels. However, these codes are instances of single-symbol decodable codes and it is natural to ask, if there exist codes other than STBCs form ODs and CIODs that allow single-symbol decoding? In this paper, the above question is answered in the affirmative by characterizing all linear STBCs, that allow single-symbol ML decoding (not necessarily full-diversity) over quasi-static fading channels-calling them single-symbol decodable designs (SDD). The class SDD includes ODs and CIODs as proper subclasses. Further, among the SDD, a class of those that offer full-diversity, called Full-rank SDD (FSDD) are characterized and classified. We then concentrate on square designs and derive the maximal rate for square FSDDs using a constructional proof. It follows that 1) except for N=2, square complex ODs are not maximal rate and 2) a rate one square FSDD exist only for two and four transmit antennas. For nonsquare designs, generalized coordinate-interleaved orthogonal designs (a superset of CIODs) are presented and analyzed. Finally, for rapid-fading channels an equivalent matrix channel representation is developed, which allows the results of quasi-static fading channels to be applied to rapid-fading channels. Using this representation we show that for rapid-fading channels the rate of single-symbol decodable STBCs are independent of the number of transmit antennas and inversely proportional to the block-length of the code. Significantly, the CIOD for two transmit antennas is the only STBC that is single-symbol decodable over both quasi-static and rapid-fading channels.

We present a new class of space-time-frequency block codes (STFBC) for multiantenna orthogonal frequency division multiplexing (MIMO-OFDM) transmissions over frequency selective Rayleigh fading channels. We show that these codes admit symbol-by-symbol decoding (decoupled decoding) when the number of nonzero taps of the channel impulse response is equal to two and they admit reduced complexity (1/2 of that of known schemes) for more than two channel taps. We also present simulation results to show that our codes perform better than the known codes.

In this paper we show that the maximal rates of square quasiorthogonal designs (QOD) is upper bounded by 2a/2afor N=2atransmit antennas. We also show that known constructions of QODs achieve this bound with equality and are therefore maximal-rate QODs

It is shown that two theorems regarding the existence of generalized linear processing orthogonal designs (GLPOD) are valid under more general conditions than those for which they have been stated and proved (for original paper see V. Tarokh et al., "Space-time block codes from orthogonal designs", ibid., vol. 45, p. 1456-1467 (1999)).

Space-time block codes (STBC) from orthogonal designs (OD), quasi-orthogonal designs (QOD) and co-ordinate interleaved orthogonal designs (CIOD) have been attracting wider attention due to their amenability for fast (single-symbol decoding for OD, CIOD and double-symbol decoding for QOD) ML decoding, and rate-one with full-rank over quasi-static fading channels. The importance of CIOD is due to the fact that, rate-one, full-rank, square ODs for arbitrary complex constellations exist only for 2 transmit antennas while such a CIOD exists for 2,3 and 4 transmit antennas with a slight restriction on the complex constellations (Zafar Ali Khan and B. Sundar Rajan, Proc. IEEE ISIT 2002, p.275, 2002; DRDO-IISc Tech. Report No. TR-PME-2002-17, 2002). These limitations motivate study of rectangular (non-square) designs. One way of obtaining rectangular designs is by deleting columns from square or non-square ODs or CIODs. We present a new construction of rectangular single-symbol decodable designs that have higher maximum mutual information than those obtained by deleting columns of CIODs and has lower peak-to-average-power ratio (PAPR). Simulation results are presented for three and five transmit antennas and compared with that of OD, QOD, CIOD to demonstrate the superiority of the proposed rectangular designs.

The diversity order is crucial for the performance of communication systems over fading channels. It has been shown by Zehavi (1992) that the diversity and hence performance of coded modulation over fading channels can be improved by bit-wise interleaving at the encoder output, and by using an appropriate soft decision metric as an input to the Viterbi decoder. A related approach is coordinate interleaving whereby the signal space coordinates are interleaved before transmission. In this paper we combine both bit interleaving and coordinate interleaving to increase the diversity order. The resulting system is referred to here as bit and coordinate interleaved coded modulation (BCICM). The pairwise probability of error is also derived, which shows that by proper design the diversity order can be doubled over bit interleaved coded modulation (BICM), for two dimensional signal sets. Simulation results for rate 2/3, 4-state 8-PSK coded modulation schemes show that BCICM significantly outperforms all known coded modulation (symbol or bit interleaved) schemes.